diff --git a/.github/workflows/cla.yml b/.github/workflows/cla.yml index c0e1544..5793f13 100644 --- a/.github/workflows/cla.yml +++ b/.github/workflows/cla.yml @@ -8,6 +8,7 @@ on: jobs: cla-check: + if: github.repository_owner == 'mlcommons' runs-on: ubuntu-latest steps: - name: "MLCommons CLA bot check" diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml new file mode 100644 index 0000000..7ae13b5 --- /dev/null +++ b/.github/workflows/publish.yml @@ -0,0 +1,31 @@ +name: Publish visualization site + + +on: + release: + types: [published] + push: + branches: + - mlperf-inference-results-scc24 + - docs + +jobs: + + publish: + name: Publish the site + runs-on: ubuntu-latest + + steps: + - name: Checkout repository normally + uses: actions/checkout@v3 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: "3.11" + + - name: Init docs site + run: bash run.sh + + - name: Run Mkdocs deploy + run: mkdocs gh-deploy --force diff --git a/.github/workflows/run-mlperf-inference-submission-checker.yml b/.github/workflows/run-mlperf-inference-submission-checker.yml new file mode 100644 index 0000000..b037c6b --- /dev/null +++ b/.github/workflows/run-mlperf-inference-submission-checker.yml @@ -0,0 +1,31 @@ +# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions + +name: MLPerf inference submission checker + +on: + pull_request: + branches: [ "main", "mlperf-inference-results-scc24" ] + +jobs: + build: + + runs-on: ubuntu-latest + env: + CM_INDEX: "on" + strategy: + fail-fast: false + matrix: + python-version: [ "3.10" ] + + steps: + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v3 + with: + python-version: ${{ matrix.python-version }} + - name: Install dependencies + run: | + python3 -m pip install cm4mlops + - name: Run MLPerf Inference Submission Checker + run: | + cm run script --tags=run,mlperf,inference,submission,checker,_short-run --adr.submission-checker-src.tags=_repo.https://github.com/gateoverflow/inference --src_version=v4.1 --quiet --extra_args=" --skip-extra-files-in-root-check" --submission_dir=./ diff --git a/.github/workflows/update-results.yml b/.github/workflows/update-results.yml new file mode 100644 index 0000000..f60d8d0 --- /dev/null +++ b/.github/workflows/update-results.yml @@ -0,0 +1,51 @@ +# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions + +name: MLPerf inference results updater + + +on: + push: + branches: [ "main", "mlperf-inference-results-scc24" ] + +jobs: + build: + + runs-on: ubuntu-latest + env: + CM_INDEX: "on" + strategy: + fail-fast: false + matrix: + python-version: [ "3.10" ] + + steps: + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v3 + with: + python-version: ${{ matrix.python-version }} + + - name: Install dependencies + run: | + python3 -m pip install cm4mlops + + - name: Run MLPerf Inference Submission Checker and generate results summary + run: | + cm run script --tags=run,mlperf,inference,submission,checker,_short-run --src_version=v4.1 --adr.submission-checker-src.tags=_repo.https://github.com/gateoverflow/inference,_branch.improve_result_generation --quiet --extra_args=" --skip-extra-files-in-root-check" --submission_dir=./ > >(tee -a out.txt) 2> >(tee -a checker_log.txt >&2) + cm run script --tags=convert,from-csv,to-md --csv_file=summary.csv --md_file=README.md + + USER="GitHub Action" + EMAIL=action@github.com + + git config --global user.name "$USER" + git config --global user.email "$EMAIL" + git remote set-url origin https://x-access-token:${{ secrets.GITHUB_TOKEN_TOKEN }}@github.com/${{ github.repository }} + git add summary* + echo -e 'Please download [summary.xlsx](summary.xlsx) to view the most recent results. \n ```' > temp + tail -n 16 checker_log.txt >> temp + echo -e '\n```\n' >> temp + cat temp | cat - README.md > temp1 + head -n 100 temp1 > README.md + git add README.md + + git diff-index --quiet HEAD || (git commit -am "Updated results summary" && git push origin) diff --git a/README.md b/README.md new file mode 100644 index 0000000..8f053e0 --- /dev/null +++ b/README.md @@ -0,0 +1,31 @@ +Please download [summary.xlsx](summary.xlsx) to view the most recent results. + ``` +[2024-10-06 03:29:53,417 submission_checker1.py:2936 INFO] Results=8, NoResults=0, Power Results=0 +[2024-10-06 03:29:53,417 submission_checker1.py:2943 INFO] --- +[2024-10-06 03:29:53,417 submission_checker1.py:2944 INFO] Closed Results=0, Closed Power Results=0 + +[2024-10-06 03:29:53,418 submission_checker1.py:2949 INFO] Open Results=8, Open Power Results=0 + +[2024-10-06 03:29:53,418 submission_checker1.py:2954 INFO] Network Results=0, Network Power Results=0 + +[2024-10-06 03:29:53,418 submission_checker1.py:2959 INFO] --- +[2024-10-06 03:29:53,418 submission_checker1.py:2961 INFO] Systems=7, Power Systems=0 +[2024-10-06 03:29:53,418 submission_checker1.py:2962 INFO] Closed Systems=0, Closed Power Systems=0 +[2024-10-06 03:29:53,418 submission_checker1.py:2967 INFO] Open Systems=7, Open Power Systems=0 +[2024-10-06 03:29:53,418 submission_checker1.py:2972 INFO] Network Systems=0, Network Power Systems=0 +[2024-10-06 03:29:53,418 submission_checker1.py:2977 INFO] --- +[2024-10-06 03:29:53,418 submission_checker1.py:2982 INFO] SUMMARY: submission looks OK +INFO:root: ! call "postprocess" from /home/runner/CM/repos/mlcommons@cm4mlops/script/run-mlperf-inference-submission-checker/customize.py + +``` + +| | Organization | Availability | Division | SystemType | SystemName | Platform | Model | MlperfModel | Scenario | Result | Accuracy | number_of_nodes | host_processor_model_name | host_processors_per_node | host_processor_core_count | accelerator_model_name | accelerators_per_node | Location | framework | operating_system | notes | compliance | errors | version | inferred | has_power | Units | weight_data_types | +|---:|:---------------|:---------------|:-----------|:-------------|:-------------|:-------------------------------------------------------|:--------------------|:--------------------|:-----------|----------:|:--------------------------------------------------------------|------------------:|:----------------------------|---------------------------:|----------------------------:|:-------------------------|------------------------:|:----------------------------------------------------------------------------------------------------------|:---------------|:------------------------------------------------|:----------------------------------|-------------:|---------:|:----------|-----------:|:------------|:----------|:--------------------| +| 0 | MLCommons | available | open | datacenter | 48ed6105bd85 | 48ed6105bd85-nvidia-gpu-TensorRT-scc24-main | stable-diffusion-xl | stable-diffusion-xl | Offline | 1.13292 | CLIP_SCORE: 15.586050063371658 FID_SCORE: 236.8087101317688 | 1 | Intel(R) Xeon(R) w7-2495X | 1 | 24 | NVIDIA GeForce RTX 4090 | 1 | open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline | TensorRT | Ubuntu 20.04 (linux-6.2.0-39-generic-glibc2.31) | Automated by MLCommons CM v2.3.6. | 1 | 0 | v4.1 | 0 | False | Samples/s | int8 | +| 1 | MLCommons | available | open | datacenter | e8dbfdd7ca14 | e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base | stable-diffusion-xl | stable-diffusion-xl | Offline | 1.13521 | CLIP_SCORE: 15.617164582014084 FID_SCORE: 233.28573789198563 | 1 | Intel(R) Xeon(R) w7-2495X | 1 | 24 | NVIDIA GeForce RTX 4090 | 1 | open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline | TensorRT | Ubuntu 20.04 (linux-6.2.0-39-generic-glibc2.31) | Automated by MLCommons CM v2.3.9. | 1 | 0 | v4.1 | 0 | False | Samples/s | int8 | +| 2 | MLCommons | available | open | datacenter | 48ed6105bd85 | 48ed6105bd85-nvidia-gpu-TensorRT-scc24-base | stable-diffusion-xl | stable-diffusion-xl | Offline | 1.13598 | CLIP_SCORE: 15.586050063371658 FID_SCORE: 236.8087101317688 | 1 | Intel(R) Xeon(R) w7-2495X | 1 | 24 | NVIDIA GeForce RTX 4090 | 1 | open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline | TensorRT | Ubuntu 20.04 (linux-6.2.0-39-generic-glibc2.31) | Automated by MLCommons CM v2.3.6. | 1 | 0 | v4.1 | 0 | False | Samples/s | int8 | +| 3 | MLCommons | available | open | edge | gh_action | gh_action-reference-gpu-pytorch_v2.4.1-default_config | gptj-99 | gptj-99 | Offline | 52.9478 | nan | 1 | Intel(R) Xeon(R) w7-2495X | 1 | 24 | NVIDIA GeForce RTX 4090 | 1 | open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline | pytorch v2.4.1 | Ubuntu 22.04 (linux-6.2.0-39-generic-glibc2.35) | Automated by MLCommons CM v2.3.4. | 1 | 0 | v4.1 | 0 | False | Tokens/s | fp32 | +| 4 | MLCommons | available | open | edge | gh_action | gh_action-reference-gpu-pytorch_v2.4.1-default_config | stable-diffusion-xl | stable-diffusion-xl | Offline | 0.345721 | CLIP_SCORE: 15.18544016778469 FID_SCORE: 235.69504308101006 | 1 | Intel(R) Xeon(R) w7-2495X | 1 | 24 | NVIDIA GeForce RTX 4090 | 1 | open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline | pytorch v2.4.1 | Ubuntu 22.04 (linux-6.2.0-39-generic-glibc2.35) | Automated by MLCommons CM v2.3.4. | 1 | 0 | v4.1 | 0 | False | Samples/s | fp32 | +| 5 | MLCommons | available | open | datacenter | 48ed6105bd85 | 48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base | stable-diffusion-xl | stable-diffusion-xl | Offline | 0.373636 | CLIP_SCORE: 15.236237794160843 FID_SCORE: 238.78369342212613 | 1 | Intel(R) Xeon(R) w7-2495X | 1 | 24 | NVIDIA GeForce RTX 4090 | 1 | open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline | TensorRT | Ubuntu 20.04 (linux-6.2.0-39-generic-glibc2.31) | Automated by MLCommons CM v2.3.6. | 1 | 0 | v4.1 | 0 | False | Samples/s | fp32 | +| 6 | MLCommons | available | open | datacenter | f9ac88850adc | f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base | stable-diffusion-xl | stable-diffusion-xl | Offline | 0.376944 | CLIP_SCORE: 15.18544016778469 FID_SCORE: 235.69504308101006 | 1 | Intel(R) Xeon(R) w7-2495X | 1 | 24 | NVIDIA GeForce RTX 4090 | 1 | open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline | pytorch v2.4.1 | Ubuntu 22.04 (linux-6.2.0-39-generic-glibc2.35) | Automated by MLCommons CM v2.3.9. | 1 | 0 | v4.1 | 0 | False | Samples/s | fp32 | +| 7 | MLCommons | available | open | datacenter | 3b07702db56d | 3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base | stable-diffusion-xl | stable-diffusion-xl | Offline | 0.374495 | CLIP_SCORE: 15.18544016778469 FID_SCORE: 235.69504308101006 | 1 | Intel(R) Xeon(R) w7-2495X | 1 | 24 | NVIDIA GeForce RTX 4090 | 1 | open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline | pytorch v2.4.1 | Ubuntu 22.04 (linux-6.2.0-39-generic-glibc2.35) | Automated by MLCommons CM v2.3.9. | 1 | 0 | v4.1 | 0 | False | Samples/s | fp32 | \ No newline at end of file diff --git a/dbversion b/dbversion new file mode 100644 index 0000000..29d6383 --- /dev/null +++ b/dbversion @@ -0,0 +1 @@ +100 diff --git a/docinit.sh b/docinit.sh new file mode 100644 index 0000000..788ebb4 --- /dev/null +++ b/docinit.sh @@ -0,0 +1,43 @@ +#!/bin/bash + +if [ ! -e docs ]; then + git clone https://github.com/GATEOverflow/inference_results_visualization_template.git docs + test $? -eq 0 || exit $? +fi + +python3 -m pip install -r docs/requirements.txt + +if [ ! -e overrides ]; then + cp -r docs/overrides overrides + test $? -eq 0 || exit $? +fi + +repo_owner=${INFERENCE_RESULTS_REPO_OWNER:-mlcommons} +repo_branch=${INFERENCE_RESULTS_REPO_BRANCH:-main} +repo_name=${INFERENCE_RESULTS_REPO_NAME:-inference_results_${INFERENCE_RESULTS_VERSION}} +ver_num=$(cat dbversion) +let ver_num++ +echo "ver_num=$ver_num" > dbversion +if [ ! -e docs/javascripts/config.js ]; then + if [ -n "${INFERENCE_RESULTS_VERSION}" ]; then + echo "const results_version=\"${INFERENCE_RESULTS_VERSION}\";" > docs/javascripts/config.js; + echo "var repo_owner=\"${repo_owner}\";" >> docs/javascripts/config.js; + echo "var repo_branch=\"${repo_branch}\";" >> docs/javascripts/config.js; + echo "var repo_name=\"${repo_name}\";" >> docs/javascripts/config.js; + #ver_num=`echo ${INFERENCE_RESULTS_VERSION} | tr -cd '0-9'` + echo "const dbVersion =\"${ver_num}\";" >> docs/javascripts/config.js; + else + echo "Please export INFERENCE_RESULTS_VERSION=v4.1 or the corresponding version"; + exit 1 + fi +fi + +if [ ! -e docs/thirdparty/tablesorter ]; then + cd docs/thirdparty && git clone https://github.com/Mottie/tablesorter.git && cd - + test $? -eq 0 || exit $? +fi + +python3 process.py +test $? -eq 0 || exit $? +python3 process_results_table.py +test $? -eq 0 || exit $? diff --git a/mkdocs.yml b/mkdocs.yml new file mode 100644 index 0000000..5a62d60 --- /dev/null +++ b/mkdocs.yml @@ -0,0 +1,43 @@ +site_name: MLPerf Inference Results Comparison +repo_url: https://github.com/mlcommons/cm4mlperf-inference +theme: + name: material + logo: img/logo_v2.svg + favicon: img/logo_v2.svg + palette: + primary: deep purple + accent: yellow + custom_dir: overrides + features: + - content.tabs.link + - content.code.copy + - navigation.expand + - navigation.sections + - navigation.indexes + - navigation.instant + - navigation.tabs + - navigation.tabs.sticky + - navigation.top + - toc.follow +nav: + - Results: index.md + - Compare: compare/index.md + - Top Results: top_results/index.md + +markdown_extensions: + - pymdownx.tasklist: + custom_checkbox: true + - pymdownx.details + - admonition + - attr_list + - def_list + - footnotes + - pymdownx.superfences: + custom_fences: + - name: mermaid + class: mermaid + format: !!python/name:pymdownx.superfences.fence_code_format + - pymdownx.tabbed: + alternate_style: true +plugins: + - macros diff --git a/open/MLCommons/code/gptj-99/README.md b/open/MLCommons/code/gptj-99/README.md new file mode 100644 index 0000000..2fd9f95 --- /dev/null +++ b/open/MLCommons/code/gptj-99/README.md @@ -0,0 +1 @@ +TBD \ No newline at end of file diff --git a/open/MLCommons/code/stable-diffusion-xl/README.md b/open/MLCommons/code/stable-diffusion-xl/README.md new file mode 100644 index 0000000..2fd9f95 --- /dev/null +++ b/open/MLCommons/code/stable-diffusion-xl/README.md @@ -0,0 +1 @@ +TBD \ No newline at end of file diff --git a/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/README.md b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/README.md new file mode 100644 index 0000000..d56d6b9 --- /dev/null +++ b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|-----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (15.18544, 235.69504) | 0.374 | - | \ No newline at end of file diff --git a/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base.json b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base.json new file mode 100644 index 0000000..d47b6cc --- /dev/null +++ b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base.json @@ -0,0 +1,7 @@ +{ + "starting_weights_filename": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0", + "retraining": "no", + "input_data_types": "fp32", + "weight_data_types": "fp32", + "weight_transformations": "no" +} \ No newline at end of file diff --git a/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/README.md b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..f0c8fc2 --- /dev/null +++ b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/README.md @@ -0,0 +1,94 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.35 +* CPU version: x86_64 +* Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] +* MLCommons CM version: 2.3.9 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo gateoverflow@cm4mlops --checkout=eac7598c2b35fb8e28ab00345d5d3c5cbdb8bb43 + +cm run script \ + --tags=app,mlperf,inference,generic,_reference,_sdxl,_pytorch,_cuda,_test,_r4.1-dev_default,_float16,_offline \ + --quiet=true \ + --env.CM_MLPERF_MODEL_SDXL_DOWNLOAD_TO_HOST=yes \ + --env.CM_QUIET=yes \ + --env.CM_MLPERF_IMPLEMENTATION=reference \ + --env.CM_MLPERF_MODEL=sdxl \ + --env.CM_MLPERF_RUN_STYLE=test \ + --env.CM_MLPERF_BACKEND=pytorch \ + --env.CM_MLPERF_SUBMISSION_SYSTEM_TYPE=datacenter \ + --env.CM_MLPERF_CLEAN_ALL=True \ + --env.CM_MLPERF_DEVICE=cuda \ + --env.CM_MLPERF_USE_DOCKER=True \ + --env.CM_MLPERF_MODEL_PRECISION=float16 \ + --env.OUTPUT_BASE_DIR=/home/arjun/scc_gh_action_results \ + --env.CM_MLPERF_LOADGEN_SCENARIO=Offline \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/scc_gh_action_submissions \ + --env.CM_MLPERF_INFERENCE_VERSION=4.1-dev \ + --env.CM_RUN_MLPERF_INFERENCE_APP_DEFAULTS=r4.1-dev_default \ + --env.CM_MLPERF_SUBMISSION_GENERATION_STYLE=short \ + --env.CM_MLPERF_SUT_NAME_RUN_CONFIG_SUFFIX4=scc24-base \ + --env.CM_MLPERF_LOADGEN_ALL_MODES=yes \ + --env.CM_MLPERF_LAST_RELEASE=v4.0 \ + --env.CM_TMP_CURRENT_PATH=/home/arjun/actions-runner/_work/cm4mlops/cm4mlops \ + --env.CM_TMP_PIP_VERSION_STRING= \ + --env.CM_CLEAN_EXTRA_CACHE_RM_TAGS=scc24-main \ + --env.CM_MODEL=sdxl \ + --env.CM_MLPERF_LOADGEN_COMPLIANCE=no \ + --env.CM_MLPERF_CLEAN_SUBMISSION_DIR=yes \ + --env.CM_RERUN=yes \ + --env.CM_MLPERF_LOADGEN_EXTRA_OPTIONS= \ + --env.CM_MLPERF_LOADGEN_MODE=performance \ + --env.CM_MLPERF_LOADGEN_SCENARIOS,=Offline \ + --env.CM_MLPERF_LOADGEN_MODES,=performance,accuracy \ + --env.CM_OUTPUT_FOLDER_NAME=test_results \ + --add_deps_recursive.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \ + --add_deps_recursive.submission-checker.tags=_short-run \ + --add_deps_recursive.coco2014-preprocessed.tags=_size.50,_with-sample-ids \ + --add_deps_recursive.coco2014-dataset.tags=_size.50,_with-sample-ids \ + --add_deps_recursive.nvidia-preprocess-data.extra_cache_tags=scc24-base \ + --v=False \ + --print_env=False \ + --print_deps=False \ + --dump_version_info=True \ + --env.OUTPUT_BASE_DIR=/home/arjun/scc_gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/scc_gh_action_submissions \ + --env.SDXL_CHECKPOINT_PATH=/home/cmuser/CM/repos/local/cache/6be1f30ecbde4c4e/stable_diffusion_fp16 +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload gateoverflow@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo gateoverflow@cm4mlops +cm pull repo gateoverflow@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: 3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base + +Model Precision: fp32 + +### Accuracy Results +`CLIP_SCORE`: `15.18544`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `235.69504`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `0.374495` diff --git a/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy_console.out b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy_console.out new file mode 100644 index 0000000..e69de29 diff --git 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"CM_HOST_CPU_L2_CACHE_SIZE": "48 MiB (24 instances)", + "CM_HOST_CPU_L3_CACHE_SIZE": "45 MiB (1 instance)", + "CM_HOST_CPU_NUMA_NODES": "1", + "CM_HOST_CPU_TOTAL_LOGICAL_CORES": "48", + "CM_HOST_MEMORY_CAPACITY": "192G", + "CM_HOST_DISK_CAPACITY": "6.9T" +} \ No newline at end of file diff --git a/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/mlperf.conf b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/mlperf.conf new file mode 100644 index 0000000..10f7ae7 --- /dev/null +++ b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/mlperf.conf @@ -0,0 +1,98 @@ +# The format of this config file is 'key = value'. +# The key has the format 'model.scenario.key'. Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/os_info.json b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/os_info.json new file mode 100644 index 0000000..babcbc8 --- /dev/null +++ b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/os_info.json @@ -0,0 +1,30 @@ +{ + "CM_HOST_OS_TYPE": "linux", + "CM_HOST_OS_BITS": "64", + "CM_HOST_OS_FLAVOR": "ubuntu", + "CM_HOST_OS_FLAVOR_LIKE": "debian", + "CM_HOST_OS_VERSION": "22.04", + "CM_HOST_OS_KERNEL_VERSION": "6.2.0-39-generic", + "CM_HOST_OS_GLIBC_VERSION": "2.35", + "CM_HOST_OS_MACHINE": "x86_64", + "CM_HOST_OS_PACKAGE_MANAGER": "apt", + "CM_HOST_OS_PACKAGE_MANAGER_INSTALL_CMD": "DEBIAN_FRONTEND=noninteractive apt-get install -y", + "CM_HOST_OS_PACKAGE_MANAGER_UPDATE_CMD": "apt-get update -y", + "+CM_HOST_OS_DEFAULT_LIBRARY_PATH": [ + "/usr/local/lib/x86_64-linux-gnu", + "/lib/x86_64-linux-gnu", + "/usr/lib/x86_64-linux-gnu", + "/usr/lib/x86_64-linux-gnu64", + "/usr/local/lib64", + "/lib64", + "/usr/lib64", + "/usr/local/lib", + "/lib", + "/usr/lib", + "/usr/x86_64-linux-gnu/lib64", + "/usr/x86_64-linux-gnu/lib" + ], + "CM_HOST_PLATFORM_FLAVOR": "x86_64", + "CM_HOST_PYTHON_BITS": "64", + "CM_HOST_SYSTEM_NAME": "3b07702db56d" +} \ No newline at end of file diff --git a/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance_console.out b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance_console.out new file mode 100644 index 0000000..e69de29 diff --git a/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/pip_freeze.json b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/pip_freeze.json new file mode 100644 index 0000000..d5f4100 --- /dev/null +++ b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/pip_freeze.json @@ -0,0 +1,74 @@ +{ + "pip_freeze": { + "accelerate": "0.34.2", + "certifi": "2024.8.30", + "charset-normalizer": "3.3.2", + "cmind": "2.3.9", + "diffusers": "0.30.3", + "dmiparser": "5.1", + "filelock": "3.16.1", + "fsspec": "2024.9.0", + "ftfy": "6.2.3", + "giturlparse": "0.12.0", + "huggingface-hub": "0.25.1", + "idna": "3.10", + "ijson": "3.3.0", + "importlib_metadata": "8.5.0", + "Jinja2": "3.1.4", + "lightning-utilities": "0.11.7", + "Mako": "1.3.5", + "MarkupSafe": "2.1.5", + "mpmath": "1.3.0", + "networkx": "3.3", + "numpy": "1.26.4", + "nvidia-cublas-cu12": "12.1.3.1", + "nvidia-cuda-cupti-cu12": "12.1.105", + "nvidia-cuda-nvrtc-cu12": "12.1.105", + "nvidia-cuda-runtime-cu12": "12.1.105", + "nvidia-cudnn-cu12": "9.1.0.70", + "nvidia-cufft-cu12": "11.0.2.54", + "nvidia-curand-cu12": "10.3.2.106", + "nvidia-cusolver-cu12": "11.4.5.107", + 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"0.44.0", + "zipp": "3.20.2" + } +} \ No newline at end of file diff --git a/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/user.conf b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/user.conf new file mode 100644 index 0000000..21df3f1 --- /dev/null +++ b/open/MLCommons/measurements/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/user.conf @@ -0,0 +1,5 @@ +stable-diffusion-xl.Offline.target_qps = 0.05 +stable-diffusion-xl.Offline.max_query_count = 10 +stable-diffusion-xl.Offline.min_query_count = 10 +stable-diffusion-xl.Offline.min_duration = 0 +stable-diffusion-xl.Offline.sample_concatenate_permutation = 0 diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/README.md b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/README.md new file mode 100644 index 0000000..b53e0be --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|-----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (15.58605, 236.80871) | 1.136 | - | \ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base.json b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base.json new file mode 100644 index 0000000..00b5fb8 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base.json @@ -0,0 +1,7 @@ +{ + "starting_weights_filename": "https://github.com/mlcommons/cm4mlops/blob/main/script/get-ml-model-stable-diffusion/_cm.json#L174", + "retraining": "no", + "input_data_types": "int32", + "weight_data_types": "int8", + "weight_transformations": "quantization, affine fusion" +} \ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/README.md b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..7b48719 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/README.md @@ -0,0 +1,57 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.29 +* CPU version: x86_64 +* Python version: 3.8.10 (default, Sep 11 2024, 16:02:53) +[GCC 9.4.0] +* MLCommons CM version: 2.3.6 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo mlcommons@cm4mlops --checkout=0d133c9551d9b2cb5b0d10aec9114dcf92c02dd9 + +cm run script \ + --tags=run-mlperf,inference,_r4.1-dev,_short,_scc24-base \ + --model=sdxl \ + --implementation=nvidia \ + --framework=tensorrt \ + --category=edge \ + --scenario=Offline \ + --execution_mode=test \ + --device=cuda \ + --quiet \ + --precision=float16 +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload mlcommons@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo mlcommons@cm4mlops +cm pull repo mlcommons@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: 48ed6105bd85-nvidia-gpu-TensorRT-scc24-base + +Model Precision: int8 + +### Accuracy Results +`CLIP_SCORE`: `15.58605`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `236.80871`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `1.13598` diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy_console.out b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy_console.out new file mode 100644 index 0000000..e69de29 diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/cm-version-info.json b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/cm-version-info.json new file mode 100644 index 0000000..ddf4214 --- /dev/null +++ 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\ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/mlperf.conf b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/mlperf.conf new file mode 100644 index 0000000..10f7ae7 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/mlperf.conf @@ -0,0 +1,98 @@ +# The format of this config file is 'key = value'. +# The key has the format 'model.scenario.key'. Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/os_info.json b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/os_info.json new file mode 100644 index 0000000..e504202 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/os_info.json @@ -0,0 +1,30 @@ +{ + "CM_HOST_OS_TYPE": "linux", + "CM_HOST_OS_BITS": "64", + "CM_HOST_OS_FLAVOR": "ubuntu", + "CM_HOST_OS_FLAVOR_LIKE": "debian", + "CM_HOST_OS_VERSION": "20.04", + "CM_HOST_OS_KERNEL_VERSION": "6.2.0-39-generic", + "CM_HOST_OS_GLIBC_VERSION": "2.31", + "CM_HOST_OS_MACHINE": "x86_64", + "CM_HOST_OS_PACKAGE_MANAGER": "apt", + "CM_HOST_OS_PACKAGE_MANAGER_INSTALL_CMD": "DEBIAN_FRONTEND=noninteractive apt-get install -y", + "CM_HOST_OS_PACKAGE_MANAGER_UPDATE_CMD": "apt-get update -y", + "+CM_HOST_OS_DEFAULT_LIBRARY_PATH": [ + "/usr/local/lib/x86_64-linux-gnu", + "/lib/x86_64-linux-gnu", + "/usr/lib/x86_64-linux-gnu", + "/usr/lib/x86_64-linux-gnu64", + "/usr/local/lib64", + "/lib64", + "/usr/lib64", + "/usr/local/lib", + "/lib", + "/usr/lib", + "/usr/x86_64-linux-gnu/lib64", + "/usr/x86_64-linux-gnu/lib" + ], + "CM_HOST_PLATFORM_FLAVOR": "x86_64", + "CM_HOST_PYTHON_BITS": "64", + "CM_HOST_SYSTEM_NAME": "48ed6105bd85" +} \ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance_console.out b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance_console.out new file mode 100644 index 0000000..e69de29 diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/pip_freeze.json b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/pip_freeze.json new file mode 100644 index 0000000..2ddcca9 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/pip_freeze.json @@ -0,0 +1,116 @@ +{ + "pip_freeze": { + "absl-py": "2.1.0", + "accelerate": "0.34.2", + "aiohappyeyeballs": "2.4.0", + 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b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/user.conf new file mode 100644 index 0000000..21df3f1 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/user.conf @@ -0,0 +1,5 @@ +stable-diffusion-xl.Offline.target_qps = 0.05 +stable-diffusion-xl.Offline.max_query_count = 10 +stable-diffusion-xl.Offline.min_query_count = 10 +stable-diffusion-xl.Offline.min_duration = 0 +stable-diffusion-xl.Offline.sample_concatenate_permutation = 0 diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/README.md b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/README.md new file mode 100644 index 0000000..b7b7be8 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|-----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (15.58605, 236.80871) | 1.133 | - | \ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main.json b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main.json new file mode 100644 index 0000000..00b5fb8 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main.json @@ -0,0 +1,7 @@ +{ + "starting_weights_filename": "https://github.com/mlcommons/cm4mlops/blob/main/script/get-ml-model-stable-diffusion/_cm.json#L174", + "retraining": "no", + "input_data_types": "int32", + "weight_data_types": "int8", + "weight_transformations": "quantization, affine fusion" +} \ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/README.md b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..c89783a --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/README.md @@ -0,0 +1,57 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.29 +* CPU version: x86_64 +* Python version: 3.8.10 (default, Sep 11 2024, 16:02:53) +[GCC 9.4.0] +* MLCommons CM version: 2.3.6 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo mlcommons@cm4mlops --checkout=0d133c9551d9b2cb5b0d10aec9114dcf92c02dd9 + +cm run script \ + --tags=run-mlperf,inference,_r4.1-dev,_short,_scc24-main \ + --model=sdxl \ + --implementation=nvidia \ + --framework=tensorrt \ + --category=edge \ + --scenario=Offline \ + --execution_mode=test \ + --device=cuda \ + --quiet \ + --precision=float16 +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload mlcommons@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo mlcommons@cm4mlops +cm pull repo mlcommons@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: 48ed6105bd85-nvidia-gpu-TensorRT-scc24-main + +Model Precision: int8 + +### Accuracy Results +`CLIP_SCORE`: `15.58605`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `236.80871`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `1.13292` diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy_console.out b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy_console.out new file mode 100644 index 0000000..e69de29 diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/cm-version-info.json b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/cm-version-info.json new file mode 100644 index 0000000..f26b698 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/cm-version-info.json @@ -0,0 +1,534 @@ +{ + "app-mlperf-inference,d775cac873ee4231:nvidia,sdxl,tensorrt,cuda,test,r4.1-dev_default,float16,offline": [ + { + "detect,os": 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Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/os_info.json b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/os_info.json new file mode 100644 index 0000000..e504202 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/os_info.json @@ -0,0 +1,30 @@ +{ + "CM_HOST_OS_TYPE": "linux", + "CM_HOST_OS_BITS": "64", + "CM_HOST_OS_FLAVOR": "ubuntu", + "CM_HOST_OS_FLAVOR_LIKE": "debian", + "CM_HOST_OS_VERSION": "20.04", + "CM_HOST_OS_KERNEL_VERSION": "6.2.0-39-generic", + "CM_HOST_OS_GLIBC_VERSION": "2.31", + "CM_HOST_OS_MACHINE": "x86_64", + "CM_HOST_OS_PACKAGE_MANAGER": "apt", + "CM_HOST_OS_PACKAGE_MANAGER_INSTALL_CMD": "DEBIAN_FRONTEND=noninteractive apt-get install -y", + "CM_HOST_OS_PACKAGE_MANAGER_UPDATE_CMD": "apt-get update -y", + "+CM_HOST_OS_DEFAULT_LIBRARY_PATH": [ + "/usr/local/lib/x86_64-linux-gnu", + "/lib/x86_64-linux-gnu", + "/usr/lib/x86_64-linux-gnu", + "/usr/lib/x86_64-linux-gnu64", + "/usr/local/lib64", + "/lib64", + "/usr/lib64", + "/usr/local/lib", + "/lib", + "/usr/lib", + "/usr/x86_64-linux-gnu/lib64", + "/usr/x86_64-linux-gnu/lib" + ], + "CM_HOST_PLATFORM_FLAVOR": "x86_64", + "CM_HOST_PYTHON_BITS": "64", + "CM_HOST_SYSTEM_NAME": "48ed6105bd85" +} \ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance_console.out b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance_console.out new file mode 100644 index 0000000..e69de29 diff --git a/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/pip_freeze.json b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/pip_freeze.json new file mode 100644 index 0000000..2ddcca9 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/pip_freeze.json @@ -0,0 +1,116 @@ +{ + "pip_freeze": { + "absl-py": "2.1.0", + "accelerate": "0.34.2", + "aiohappyeyeballs": "2.4.0", + 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b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/user.conf new file mode 100644 index 0000000..21df3f1 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/user.conf @@ -0,0 +1,5 @@ +stable-diffusion-xl.Offline.target_qps = 0.05 +stable-diffusion-xl.Offline.max_query_count = 10 +stable-diffusion-xl.Offline.min_query_count = 10 +stable-diffusion-xl.Offline.min_duration = 0 +stable-diffusion-xl.Offline.sample_concatenate_permutation = 0 diff --git a/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/README.md b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/README.md new file mode 100644 index 0000000..2da64e1 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|-----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (15.23624, 238.78369) | 0.374 | - | \ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base.json b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base.json new file mode 100644 index 0000000..d47b6cc --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base.json @@ -0,0 +1,7 @@ +{ + "starting_weights_filename": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0", + "retraining": "no", + "input_data_types": "fp32", + "weight_data_types": "fp32", + "weight_transformations": "no" +} \ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/README.md b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..5bab4b1 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/README.md @@ -0,0 +1,57 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.29 +* CPU version: x86_64 +* Python version: 3.8.10 (default, Sep 11 2024, 16:02:53) +[GCC 9.4.0] +* MLCommons CM version: 2.3.6 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo mlcommons@cm4mlops --checkout=735b581a345d5a04f8cd7195f6fbff3a37c538d8 + +cm run script \ + --tags=run-mlperf,inference,_r4.1-dev,_short,_scc24-base \ + --model=sdxl \ + --implementation=reference \ + --framework=pytorch \ + --category=datacenter \ + --scenario=Offline \ + --execution_mode=test \ + --device=cuda \ + --quiet \ + --precision=float16 +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload mlcommons@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo mlcommons@cm4mlops +cm pull repo mlcommons@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: 48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base + +Model Precision: fp32 + +### Accuracy Results +`CLIP_SCORE`: `15.23624`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `238.78369`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `0.373636` diff --git a/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy_console.out b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy_console.out new file mode 100644 index 0000000..e69de29 diff --git a/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/cm-version-info.json b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/cm-version-info.json new file mode 100644 index 0000000..fe63fb1 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/cm-version-info.json @@ -0,0 +1,464 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Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/os_info.json 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"zipp": "3.20.2" + } +} \ No newline at end of file diff --git a/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/user.conf b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/user.conf new file mode 100644 index 0000000..21df3f1 --- /dev/null +++ b/open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/user.conf @@ -0,0 +1,5 @@ +stable-diffusion-xl.Offline.target_qps = 0.05 +stable-diffusion-xl.Offline.max_query_count = 10 +stable-diffusion-xl.Offline.min_query_count = 10 +stable-diffusion-xl.Offline.min_duration = 0 +stable-diffusion-xl.Offline.sample_concatenate_permutation = 0 diff --git a/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/README.md b/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/README.md new file mode 100644 index 0000000..1d9ea6e --- /dev/null +++ b/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|-----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (15.61716, 233.28574) | 1.135 | - | \ No newline at end of file diff --git a/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/README.md b/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..d717073 --- /dev/null +++ b/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/README.md @@ -0,0 +1,96 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.29 +* CPU version: x86_64 +* Python version: 3.8.10 (default, Sep 11 2024, 16:02:53) +[GCC 9.4.0] +* MLCommons CM version: 2.3.9 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo gateoverflow@cm4mlops --checkout=eac7598c2b35fb8e28ab00345d5d3c5cbdb8bb43 + +cm run script \ + --tags=app,mlperf,inference,generic,_nvidia,_sdxl,_tensorrt,_test,_r4.1-dev_default,_float16,_offline \ + --quiet=true \ + --env.CM_MLPERF_MODEL_SDXL_DOWNLOAD_TO_HOST=yes \ + --env.CM_QUIET=yes \ + --env.CM_MLPERF_IMPLEMENTATION=nvidia \ + --env.CM_MLPERF_MODEL=sdxl \ + --env.CM_MLPERF_RUN_STYLE=test \ + --env.CM_MLPERF_BACKEND=tensorrt \ + --env.CM_MLPERF_SUBMISSION_SYSTEM_TYPE=datacenter \ + --env.CM_MLPERF_CLEAN_ALL=True \ + --env.CM_MLPERF_DEVICE= \ + --env.CM_MLPERF_USE_DOCKER=True \ + --env.CM_MLPERF_MODEL_PRECISION=float16 \ + --env.OUTPUT_BASE_DIR=/home/arjun/scc_gh_action_results \ + --env.CM_MLPERF_LOADGEN_SCENARIO=Offline \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/scc_gh_action_submissions \ + --env.CM_MLPERF_INFERENCE_VERSION=4.1-dev \ + --env.CM_RUN_MLPERF_INFERENCE_APP_DEFAULTS=r4.1-dev_default \ + --env.CM_MLPERF_SUBMISSION_GENERATION_STYLE=short \ + --env.CM_MLPERF_SUT_NAME_RUN_CONFIG_SUFFIX4=scc24-base \ + --env.CM_MLPERF_LOADGEN_ALL_MODES=yes \ + --env.CM_MLPERF_LAST_RELEASE=v4.0 \ + --env.CM_TMP_CURRENT_PATH=/home/arjun/actions-runner/_work/cm4mlops/cm4mlops \ + --env.CM_TMP_PIP_VERSION_STRING= \ + --env.CM_CLEAN_EXTRA_CACHE_RM_TAGS=scc24-main \ + --env.CM_MODEL=sdxl \ + --env.CM_MLPERF_LOADGEN_COMPLIANCE=no \ + --env.CM_MLPERF_CLEAN_SUBMISSION_DIR=yes \ + --env.CM_RERUN=yes \ + --env.CM_MLPERF_LOADGEN_EXTRA_OPTIONS= \ + --env.CM_MLPERF_LOADGEN_MODE=performance \ + --env.CM_MLPERF_LOADGEN_SCENARIOS,=Offline \ + --env.CM_MLPERF_LOADGEN_MODES,=performance,accuracy \ + --env.CM_OUTPUT_FOLDER_NAME=test_results \ + --add_deps_recursive.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \ + --add_deps_recursive.submission-checker.tags=_short-run \ + --add_deps_recursive.coco2014-preprocessed.tags=_size.50,_with-sample-ids \ + --add_deps_recursive.coco2014-dataset.tags=_size.50,_with-sample-ids \ + --add_deps_recursive.nvidia-preprocess-data.extra_cache_tags=scc24-base \ + --v=False \ + --print_env=False \ + --print_deps=False \ + --dump_version_info=True \ + --env.OUTPUT_BASE_DIR=/home/arjun/scc_gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/scc_gh_action_submissions \ + --env.SDXL_CHECKPOINT_PATH=/home/cmuser/CM/repos/local/cache/6be1f30ecbde4c4e/stable_diffusion_fp16 \ + --env.MLPERF_SCRATCH_PATH=/home/cmuser/CM/repos/local/cache/e066920512fd47b7 +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload gateoverflow@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo gateoverflow@cm4mlops +cm pull repo gateoverflow@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base + +Model Precision: int8 + +### Accuracy Results +`CLIP_SCORE`: `15.61716`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `233.28574`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `1.13521` diff --git a/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy_console.out 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"https://github.com/mlcommons/cm4mlops/blob/main/script/get-ml-model-stable-diffusion/_cm.json#L174", + "retraining": "no", + "input_data_types": "int32", + "weight_data_types": "int8", + "weight_transformations": "quantization, affine fusion" +} \ No newline at end of file diff --git a/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/mlperf.conf b/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/mlperf.conf new file mode 100644 index 0000000..10f7ae7 --- /dev/null +++ b/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/mlperf.conf @@ -0,0 +1,98 @@ +# The format of this config file is 'key = value'. +# The key has the format 'model.scenario.key'. Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/os_info.json b/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/os_info.json new file 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b/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/user.conf new file mode 100644 index 0000000..21df3f1 --- /dev/null +++ b/open/MLCommons/measurements/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/user.conf @@ -0,0 +1,5 @@ +stable-diffusion-xl.Offline.target_qps = 0.05 +stable-diffusion-xl.Offline.max_query_count = 10 +stable-diffusion-xl.Offline.min_query_count = 10 +stable-diffusion-xl.Offline.min_duration = 0 +stable-diffusion-xl.Offline.sample_concatenate_permutation = 0 diff --git a/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/README.md b/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/README.md new file mode 100644 index 0000000..a19744e --- /dev/null +++ b/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|-----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (15.18544, 235.69504) | 0.377 | - | \ No newline at end of file diff --git a/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/README.md b/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..fac8336 --- /dev/null +++ b/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/README.md @@ -0,0 +1,93 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.35 +* CPU version: x86_64 +* Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] +* MLCommons CM version: 2.3.9 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo gateoverflow@cm4mlops --checkout=fbf3832ede608facaca37f10b603cbe65f7275eb + +cm run script \ + --tags=app,mlperf,inference,generic,_reference,_sdxl,_pytorch,_cuda,_test,_r4.1-dev_default,_float16,_offline \ + --quiet=true \ + --env.CM_MLPERF_MODEL_SDXL_DOWNLOAD_TO_HOST=yes \ + --env.CM_QUIET=yes \ + --env.CM_MLPERF_IMPLEMENTATION=reference \ + --env.CM_MLPERF_MODEL=sdxl \ + --env.CM_MLPERF_RUN_STYLE=test \ + --env.CM_MLPERF_BACKEND=pytorch \ + --env.CM_MLPERF_SUBMISSION_SYSTEM_TYPE=datacenter \ + --env.CM_MLPERF_CLEAN_ALL=True \ + --env.CM_MLPERF_DEVICE=cuda \ + --env.CM_MLPERF_USE_DOCKER=True \ + --env.CM_MLPERF_MODEL_PRECISION=float16 \ + --env.OUTPUT_BASE_DIR=/home/arjun/scc_gh_action_results \ + --env.CM_MLPERF_LOADGEN_SCENARIO=Offline \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/scc_gh_action_submissions \ + --env.CM_MLPERF_INFERENCE_VERSION=4.1-dev \ + --env.CM_RUN_MLPERF_INFERENCE_APP_DEFAULTS=r4.1-dev_default \ + --env.CM_MLPERF_SUBMISSION_GENERATION_STYLE=short \ + --env.CM_MLPERF_SUT_NAME_RUN_CONFIG_SUFFIX4=scc24-base \ + --env.CM_MLPERF_LOADGEN_ALL_MODES=yes \ + --env.CM_MLPERF_LAST_RELEASE=v4.0 \ + --env.CM_TMP_PIP_VERSION_STRING= \ + --env.CM_CLEAN_EXTRA_CACHE_RM_TAGS=scc24-main \ + --env.CM_MODEL=sdxl \ + --env.CM_MLPERF_LOADGEN_COMPLIANCE=no \ + --env.CM_MLPERF_CLEAN_SUBMISSION_DIR=yes \ + --env.CM_RERUN=yes \ + --env.CM_MLPERF_LOADGEN_EXTRA_OPTIONS= \ + --env.CM_MLPERF_LOADGEN_MODE=performance \ + --env.CM_MLPERF_LOADGEN_SCENARIOS,=Offline \ + --env.CM_MLPERF_LOADGEN_MODES,=performance,accuracy \ + --env.CM_OUTPUT_FOLDER_NAME=test_results \ + --add_deps_recursive.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \ + --add_deps_recursive.submission-checker.tags=_short-run \ + --add_deps_recursive.coco2014-preprocessed.tags=_size.50,_with-sample-ids \ + --add_deps_recursive.coco2014-dataset.tags=_size.50,_with-sample-ids \ + --add_deps_recursive.nvidia-preprocess-data.extra_cache_tags=scc24-base \ + --v=False \ + --print_env=False \ + --print_deps=False \ + --dump_version_info=True \ + --env.OUTPUT_BASE_DIR=/home/arjun/scc_gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/scc_gh_action_submissions \ + --env.SDXL_CHECKPOINT_PATH=/home/cmuser/CM/repos/local/cache/6be1f30ecbde4c4e/stable_diffusion_fp16 +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload gateoverflow@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo gateoverflow@cm4mlops +cm pull repo gateoverflow@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base + +Model Precision: fp32 + +### Accuracy Results +`CLIP_SCORE`: `15.18544`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `235.69504`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `0.376944` diff --git a/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy_console.out b/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy_console.out new file mode 100644 index 0000000..e69de29 diff --git a/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/cm-version-info.json 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Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/MLCommons/measurements/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/os_info.json 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/dev/null +++ b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|-----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (15.18544, 235.69504) | 0.346 | - | \ No newline at end of file diff --git a/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/README.md b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/README.md new file mode 100644 index 0000000..0f6c68f --- /dev/null +++ b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/README.md @@ -0,0 +1,100 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.35 +* CPU version: x86_64 +* Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] +* MLCommons CM version: 2.3.6 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo gateoverflow@cm4mlops --checkout=042079b83034d5232464795a48aec3ec497dbbd1 + +cm run script \ + --tags=app,mlperf,inference,generic,_reference,_gptj-99,_pytorch,_cuda,_test,_r4.1-dev_default,_bfloat16,_offline \ + --quiet=true \ + --env.CM_QUIET=yes \ + --env.CM_MLPERF_IMPLEMENTATION=reference \ + --env.CM_MLPERF_MODEL=gptj-99 \ + --env.CM_MLPERF_RUN_STYLE=test \ + --env.CM_MLPERF_BACKEND=pytorch \ + --env.GPTJ_BEAM_SIZE=1 \ + --env.CM_MLPERF_CLEAN_ALL=True \ + --env.CM_MLPERF_DEVICE=cuda \ + --env.CM_MLPERF_USE_DOCKER=True \ + --env.CM_HW_NAME=gh_action \ + --env.CM_MLPERF_MODEL_PRECISION=bfloat16 \ + --env.OUTPUT_BASE_DIR=/home/arjun/gh_action_results \ + --env.CM_MLPERF_LOADGEN_SCENARIO=Offline \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/gh_action_submissions \ + --env.CM_MLPERF_SUBMITTER=MLCommons \ + --env.CM_MLPERF_LOADGEN_TARGET_QPS=1 \ + --env.CM_TEST_QUERY_COUNT=1 \ + --env.CM_MLPERF_LOADGEN_COMPLIANCE=no \ + --env.CM_MLPERF_SUBMISSION_RUN=yes \ + --env.CM_RUN_MLPERF_ACCURACY=on \ + --env.CM_RUN_SUBMISSION_CHECKER=yes \ + --env.CM_TAR_SUBMISSION_DIR=yes \ + --env.CM_MLPERF_SUBMISSION_GENERATION_STYLE=short \ + --env.CM_MLPERF_LOADGEN_ALL_MODES=yes \ + --env.CM_MLPERF_INFERENCE_VERSION=4.1-dev \ + --env.CM_RUN_MLPERF_INFERENCE_APP_DEFAULTS=r4.1-dev_default \ + --env.CM_MLPERF_LAST_RELEASE=v4.0 \ + --env.CM_TMP_CURRENT_PATH=/home/arjun/actions-runner/_work/cm4mlops/cm4mlops \ + --env.CM_TMP_PIP_VERSION_STRING= \ + --env.CM_MODEL=gptj-99 \ + --env.CM_MLPERF_CLEAN_SUBMISSION_DIR=yes \ + --env.CM_RERUN=yes \ + --env.CM_MLPERF_LOADGEN_EXTRA_OPTIONS= \ + --env.CM_MLPERF_LOADGEN_MODE=performance \ + --env.CM_MLPERF_LOADGEN_SCENARIOS,=Offline \ + --env.CM_MLPERF_LOADGEN_MODES,=performance,accuracy \ + --env.CM_OUTPUT_FOLDER_NAME=test_results \ + --add_deps_recursive.compiler.tags=gcc \ + --add_deps_recursive.submission-checker.tags=_short-run \ + --add_deps_recursive.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \ + --adr.compiler.tags=gcc \ + --adr.submission-checker.tags=_short-run \ + --adr.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \ + --adr.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \ + --adr.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \ + --v=False \ + --print_env=False \ + --print_deps=False \ + --dump_version_info=True \ + --env.OUTPUT_BASE_DIR=/home/arjun/gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/gh_action_submissions \ + --env.GPTJ_CHECKPOINT_PATH=/home/cmuser/CM/repos/local/cache/98e466fd3f2c42cc/checkpoint/checkpoint-final +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload gateoverflow@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo gateoverflow@cm4mlops +cm pull repo gateoverflow@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: gh_action-reference-gpu-pytorch_v2.4.1-default_config + +Model Precision: fp32 + +### Accuracy Results + +### Performance Results +`Samples per second`: `0.767359` diff --git a/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy_console.out 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Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/os_info.json b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/os_info.json new file mode 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b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/user.conf new file mode 100644 index 0000000..ed30c86 --- /dev/null +++ b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/user.conf @@ -0,0 +1,5 @@ +gptj.Offline.target_qps = 1.0 +gptj.Offline.max_query_count = 1 +gptj.Offline.min_query_count = 1 +gptj.Offline.min_duration = 0 +gptj.Offline.sample_concatenate_permutation = 0 diff --git a/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/README.md b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..220134f --- /dev/null +++ b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/README.md @@ -0,0 +1,100 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.35 +* CPU version: x86_64 +* Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] +* MLCommons CM version: 2.3.6 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo gateoverflow@cm4mlops --checkout=3dbea4a03583d31eb1a07a026b6b316028258643 + +cm run script \ + --tags=app,mlperf,inference,generic,_reference,_sdxl,_pytorch,_cuda,_test,_r4.1-dev_default,_float16,_offline \ + --quiet=true \ + --env.CM_QUIET=yes \ + --env.CM_MLPERF_IMPLEMENTATION=reference \ + --env.CM_MLPERF_MODEL=sdxl \ + --env.CM_MLPERF_RUN_STYLE=test \ + --env.CM_MLPERF_BACKEND=pytorch \ + --env.CM_MLPERF_CLEAN_ALL=True \ + --env.CM_MLPERF_DEVICE=cuda \ + --env.CM_MLPERF_USE_DOCKER=True \ + --env.CM_HW_NAME=gh_action \ + --env.CM_MLPERF_MODEL_PRECISION=float16 \ + --env.OUTPUT_BASE_DIR=/home/arjun/gh_action_results \ + --env.CM_MLPERF_LOADGEN_SCENARIO=Offline \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/gh_action_submissions \ + --env.CM_MLPERF_SUBMITTER=MLCommons \ + --env.CM_MLPERF_LOADGEN_TARGET_QPS=1 \ + --env.CM_TEST_QUERY_COUNT=1 \ + --env.CM_MLPERF_LOADGEN_COMPLIANCE=no \ + --env.CM_MLPERF_SUBMISSION_RUN=yes \ + --env.CM_RUN_MLPERF_ACCURACY=on \ + --env.CM_RUN_SUBMISSION_CHECKER=yes \ + --env.CM_TAR_SUBMISSION_DIR=yes \ + --env.CM_MLPERF_SUBMISSION_GENERATION_STYLE=short \ + --env.CM_MLPERF_LOADGEN_ALL_MODES=yes \ + --env.CM_MLPERF_INFERENCE_VERSION=4.1-dev \ + --env.CM_RUN_MLPERF_INFERENCE_APP_DEFAULTS=r4.1-dev_default \ + --env.CM_MLPERF_LAST_RELEASE=v4.0 \ + --env.CM_TMP_CURRENT_PATH=/home/arjun/actions-runner/_work/cm4mlops/cm4mlops \ + --env.CM_TMP_PIP_VERSION_STRING= \ + --env.CM_MODEL=sdxl \ + --env.CM_MLPERF_CLEAN_SUBMISSION_DIR=yes \ + --env.CM_RERUN=yes \ + --env.CM_MLPERF_LOADGEN_EXTRA_OPTIONS= \ + --env.CM_MLPERF_LOADGEN_MODE=performance \ + --env.CM_MLPERF_LOADGEN_SCENARIOS,=Offline \ + --env.CM_MLPERF_LOADGEN_MODES,=performance,accuracy \ + --env.CM_OUTPUT_FOLDER_NAME=test_results \ + --add_deps_recursive.compiler.tags=gcc \ + --add_deps_recursive.submission-checker.tags=_short-run \ + --add_deps_recursive.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \ + --adr.compiler.tags=gcc \ + --adr.submission-checker.tags=_short-run \ + --adr.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \ + --adr.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \ + --adr.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \ + --v=False \ + --print_env=False \ + --print_deps=False \ + --dump_version_info=True \ + --env.OUTPUT_BASE_DIR=/home/arjun/gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/gh_action_submissions +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload gateoverflow@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo gateoverflow@cm4mlops +cm pull repo gateoverflow@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: gh_action-reference-gpu-pytorch_v2.4.1-default_config + +Model Precision: fp32 + +### Accuracy Results +`CLIP_SCORE`: `15.18544`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `235.69504`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `0.345721` diff --git 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value'. +# The key has the format 'model.scenario.key'. Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/os_info.json 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"3.20.2" + } +} \ No newline at end of file diff --git a/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/user.conf b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/user.conf new file mode 100644 index 0000000..6b964a3 --- /dev/null +++ b/open/MLCommons/measurements/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/user.conf @@ -0,0 +1,5 @@ +stable-diffusion-xl.Offline.target_qps = 0.05 +stable-diffusion-xl.Offline.max_query_count = 1 +stable-diffusion-xl.Offline.min_query_count = 1 +stable-diffusion-xl.Offline.min_duration = 0 +stable-diffusion-xl.Offline.sample_concatenate_permutation = 0 diff --git a/open/MLCommons/model_mapping.json b/open/MLCommons/model_mapping.json new file mode 100644 index 0000000..0aa5fff --- /dev/null +++ b/open/MLCommons/model_mapping.json @@ -0,0 +1,3 @@ +{ + "stable-diffusion-xl": "stable-diffusion-xl" +} \ No newline at end of file diff --git a/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt new file mode 100644 index 0000000..61867ab --- /dev/null +++ b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt @@ -0,0 +1,2 @@ +Accuracy Results: {'FID_SCORE': 235.69504308101006, 'CLIP_SCORE': 15.18544016778469} +hash=52ff0ab803fb8e84330e530a1f73ff0ab9a07e7715792ead5a5a76c9d533dd3e diff --git a/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/images/1.png b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/images/1.png new file mode 100644 index 0000000..e5a6a91 Binary files /dev/null and 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"time_ms": 0.006344, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 67, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "test_datetime", "value": "2024-10-06T03:22:56Z", "time_ms": 0.016250, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1198, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "sut_name", "value": "PySUT", "time_ms": 0.016250, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1199, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "get_sut_name_duration_ns", "value": 225, "time_ms": 0.016250, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1200, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.016250, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 50, "time_ms": 0.016250, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.016250, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 270, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_test_mode", "value": "AccuracyOnly", "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 271, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 308, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 314, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 315, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_min_query_count", "value": 50, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_max_query_count", "value": 50, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 318, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 319, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 321, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_accuracy_log_rng_seed", "value": 0, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 322, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_accuracy_log_probability", "value": 0, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 324, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_accuracy_log_sampling_target", "value": 0, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 326, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_print_timestamps", "value": false, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 328, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_performance_issue_unique", "value": false, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 329, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_performance_sample_count_override", "value": 5000, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "requested_sample_concatenate_permutation", "value": false, "time_ms": 0.019224, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 337, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_scenario", "value": "Offline", "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 413, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_test_mode", "value": "AccuracyOnly", "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 414, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_samples_per_query", "value": 50, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 416, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_target_qps", "value": 0.05, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 417, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 419, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_max_async_queries", "value": 1, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 421, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_target_duration_ms", "value": 0, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 422, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_min_duration_ms", "value": 0, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 424, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_max_duration_ms", "value": 0, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 425, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_max_query_count", "value": 50, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 427, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_min_sample_count", "value": 50, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 428, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 430, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 432, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 437, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 439, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 444, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 446, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.019305, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 448, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "generic_message", "value": "Starting accuracy mode", "time_ms": 0.024470, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1090, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.030953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 1.867677, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "generated_samples_per_query", "value": 50, "time_ms": 1.867677, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 1.867677, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 133422.171186, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 133422.171186, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 133422.171186, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 133422.171186, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 133422.171186, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 133422.171186, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "power_begin", "value": "10-06-2024 03:22:56.847", "time_ms": 133422.174237, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 66514, "tid": 66514}} +:::MLLOG {"key": "power_end", "value": "10-06-2024 03:25:10.250", "time_ms": 133422.174237, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 66514, "tid": 66514}} diff --git a/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..f79a7e7 --- /dev/null +++ b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt @@ -0,0 +1,87 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.1 @ 41fa8aadd1", "time_ms": 0.007125, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-10-03T00:13:10.239379", "time_ms": 0.007125, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-10-03T00:13:10.239384", "time_ms": 0.007125, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-10-01T18:00:17+01:00", "time_ms": 0.007125, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "41fa8aadd1ba0ecc97f6a519d8b42b04278e5f24 Add format files github action (#1682)\n518b454fd8647bfbd23a074e875e87353f33393e Tflite tpu (#1449)\ne0fdec1c7a75c98cfc194f13d62ac4388d419c8a Fix link in GettingStarted.ipynb (#1512)\n92bd8198d15411d7fb7d7c27f8904bc5a0bcfe7a Fix warning in the submission checker (#1808)\n224cfbf5c0e82cae6d48620025b7e1258ae3666a Fix typo in reference datatype (#1851)", "time_ms": 0.007125, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.007125, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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"time_ms": 0.007125, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 67, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "test_datetime", "value": "2024-10-06T03:22:00Z", "time_ms": 0.017727, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1198, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "sut_name", "value": "PySUT", "time_ms": 0.017727, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1199, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "get_sut_name_duration_ns", "value": 147, "time_ms": 0.017727, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1200, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.017727, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 50, "time_ms": 0.017727, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.017727, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.021108, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 270, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "requested_test_mode", "value": "PerformanceOnly", "time_ms": 0.021108, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 271, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.021108, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 308, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.021108, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 314, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.021108, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 315, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "requested_min_query_count", "value": 10, "time_ms": 0.021108, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "requested_max_query_count", "value": 10, "time_ms": 0.021108, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.021108, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": 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"pid": 63573, "tid": 63573}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.021214, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.021214, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.021214, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 444, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.021214, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 446, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.021214, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 448, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "generic_message", "value": "Starting performance mode", "time_ms": 0.026820, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 841, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.033309, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 1.858561, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "generated_samples_per_query", "value": 10, "time_ms": 1.858561, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 1.858561, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 13467.418346, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "issue_query_controller.cc", "line_no": 482, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 26710.441810, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 26710.441810, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 26710.441810, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 26710.441810, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 26710.441810, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 26710.441810, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "power_begin", "value": "10-06-2024 03:22:00.613", "time_ms": 26710.444654, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "power_end", "value": "10-06-2024 03:22:27.316", "time_ms": 26710.444654, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 655, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 660, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 661, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 662, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "early_stopping_result", "value": "", "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 682, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_query_count", "value": 1, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 692, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_samples_per_second", "value": 0.374495, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 748, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_min_latency_ns", "value": 2899059605, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 754, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_max_latency_ns", "value": 26702635222, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 755, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 14794119289, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 756, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 16108303960, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 26702635222, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 26702635222, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 26702635222, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 26702635222, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 63573, "tid": 63573}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 26702635222, "time_ms": 26710.546008, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 63573, "tid": 63573}} diff --git a/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..153a9f0 --- /dev/null +++ b/open/MLCommons/results/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,51 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 0.374495 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 2899059605 +Max latency (ns) : 26702635222 +Mean latency (ns) : 14794119289 +50.00 percentile latency (ns) : 16108303960 +90.00 percentile latency (ns) : 26702635222 +95.00 percentile latency (ns) : 26702635222 +97.00 percentile latency (ns) : 26702635222 +99.00 percentile latency (ns) : 26702635222 +99.90 percentile latency (ns) : 26702635222 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 10 +target_qps : 0.05 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 10 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 5000 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt new file mode 100644 index 0000000..f7bc644 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt @@ -0,0 +1,2 @@ +Accuracy Results: {'FID_SCORE': 236.8087101317688, 'CLIP_SCORE': 15.586050063371658} +hash=3e0df040b48a1d30350895404d7509ad0beab075a7fdb5aa9252ace6ef8c5922 diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/images/captions.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/images/captions.txt new file mode 100644 index 0000000..102b05d --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/images/captions.txt @@ -0,0 +1,10 @@ +4655 Close up of a red fire hydrant near a sidewalk. +2569 A dark table has a large arrangement of food. +1303 A baby boy standing inside of a wooden crib. +109 People walking toward an airplane to board it. +4509 a couple of horses grazing on some green grass +3009 A horse that is standing with a cart near birds. +2179 A man holds up a Polish sausage on a bun. +1826 Two dogs resting comfortably on a tiled floor. +2094 A cat hiding in a basket of some sort. +3340 Vintage picture of a man and a horse on the farm. diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json new file mode 100644 index 0000000..09fe24b --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json @@ -0,0 +1,7 @@ +[ +{ "seq_id" : 2, "qsl_idx" : 46, "data" : 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} +] diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt new file mode 100644 index 0000000..9546d2c --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt @@ -0,0 +1,68 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.003685, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-09-19T17:52:23.329269", "time_ms": 0.003685, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-09-20T00:52:23.329275", "time_ms": 0.003685, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-02-15T15:46:50-05:00", "time_ms": 0.003685, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "486a629ea4d5c5150f452d0b0a196bf71fd2021e Hotfix: DLRMv2 Audit Test01 fallback failure (#1626)\nf9a643c0a0e920588da1b51a1d822e1071a9dbec Add number of tokens to offline (#1623)\nf06b920eac2170df38b5502c7443f50c9afa6045 Bugfix: equal-issue mode on offline causing accuracy run to fail (3D-UNet) (#1624)\n0ed5190e82e1ca1cf95626e50e61cb6678c7f2ff Fix submission checker and TEST06 for Llama2 (#1616)\n817dd961221d3ca284b024368130bd5dc5e4b54a Turn equal issue mode off for TEST06 (#1615)\n840435a1abe8be823e0a5a18ad3173bc520aa24f Update README.md with CM commands to download stable-diffusion, gptj and dlrmv2 models (#1604)\n3190d09a148bc1d72c9d946e4cf3b54db0d0e60a Typo fix in README.md (#1588)\nb0777f0bd3b7e5cd6a51d670d8b4df656cf6fb29 Update README.md - remove unwanted lines in CM commands (#1601)\nd7dba0826ac96a0e8bcae525086961e47c409a38 Remove loadgen warnings (#1608)\nd45a66c33bb0b6548d6172b38645bf94ffe24b39 Add upper limit to tokens per sample (#1612)\n44285d9a44041c3d4f7df0acf1e72c375e9fcbd2 Set completed samples per second as llama metric (#1613)\n357ccefca4db55ff373e029d5d1e3e6246bde5d4 Enable equal issue mode for LLM benchmarks (#1610)\n104d85531af7ae2a07ded36dd6e8c7f2c7746d06 Add sample length check to test06 (#1603)\n473053fc9f1b8c5edf60e11ec74607126938fbc4 Fix loadgen token metrics latency constrains (#1596)\ncc3daae3c7f18d7eedc5ffbc271d324e5aca6233 #1598: fix token and sample logging for Llama2 when accuracy_log_sampling_target is enabled (#1599)\n3a902e598e5a17013c26fea975c0a60e6d7feae1 Add support to dump 10 compliance images during accuracy run for SDXL (#1591)", "time_ms": 0.003685, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.003685, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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"pid": 157980, "tid": 157980}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 38233.864246, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 38233.864246, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 38233.864246, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 38233.864246, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "power_begin", "value": "09-23-2024 21:02:04.020", "time_ms": 38233.865730, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 157980, "tid": 157980}} +:::MLLOG {"key": "power_end", "value": "09-23-2024 21:02:42.234", "time_ms": 38233.865730, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 157980, "tid": 157980}} diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..3fd7aaf --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt @@ -0,0 +1,85 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.003595, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-09-19T17:52:23.329269", "time_ms": 0.003595, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-09-20T00:52:23.329275", "time_ms": 0.003595, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-02-15T15:46:50-05:00", "time_ms": 0.003595, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "486a629ea4d5c5150f452d0b0a196bf71fd2021e Hotfix: DLRMv2 Audit Test01 fallback failure (#1626)\nf9a643c0a0e920588da1b51a1d822e1071a9dbec Add number of tokens to offline (#1623)\nf06b920eac2170df38b5502c7443f50c9afa6045 Bugfix: equal-issue mode on offline causing accuracy run to fail (3D-UNet) (#1624)\n0ed5190e82e1ca1cf95626e50e61cb6678c7f2ff Fix submission checker and TEST06 for Llama2 (#1616)\n817dd961221d3ca284b024368130bd5dc5e4b54a Turn equal issue mode off for TEST06 (#1615)\n840435a1abe8be823e0a5a18ad3173bc520aa24f Update README.md with CM commands to download stable-diffusion, gptj and dlrmv2 models (#1604)\n3190d09a148bc1d72c9d946e4cf3b54db0d0e60a Typo fix in README.md (#1588)\nb0777f0bd3b7e5cd6a51d670d8b4df656cf6fb29 Update README.md - remove unwanted lines in CM commands (#1601)\nd7dba0826ac96a0e8bcae525086961e47c409a38 Remove loadgen warnings (#1608)\nd45a66c33bb0b6548d6172b38645bf94ffe24b39 Add upper limit to tokens per sample (#1612)\n44285d9a44041c3d4f7df0acf1e72c375e9fcbd2 Set completed samples per second as llama metric (#1613)\n357ccefca4db55ff373e029d5d1e3e6246bde5d4 Enable equal issue mode for LLM benchmarks (#1610)\n104d85531af7ae2a07ded36dd6e8c7f2c7746d06 Add sample length check to test06 (#1603)\n473053fc9f1b8c5edf60e11ec74607126938fbc4 Fix loadgen token metrics latency constrains (#1596)\ncc3daae3c7f18d7eedc5ffbc271d324e5aca6233 #1598: fix token and sample logging for Llama2 when accuracy_log_sampling_target is enabled (#1599)\n3a902e598e5a17013c26fea975c0a60e6d7feae1 Add support to dump 10 compliance images during accuracy run for SDXL (#1591)", "time_ms": 0.003595, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.003595, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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"file": "test_settings_internal.cc", "line_no": 268, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "requested_test_mode", "value": "PerformanceOnly", "time_ms": 0.043864, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 269, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.043864, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 306, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.043864, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 312, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, 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"line_no": 333, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_scenario", "value": "Offline", "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 409, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_test_mode", "value": "PerformanceOnly", "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 410, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_samples_per_query", "value": 10, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 412, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_target_qps", "value": 0.05, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 413, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 414, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 415, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_max_async_queries", "value": 1, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 417, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_target_duration_ms", "value": 0, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_min_duration_ms", "value": 0, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 420, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_max_duration_ms", "value": 0, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 421, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 422, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_max_query_count", "value": 10, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 423, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_min_sample_count", "value": 10, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 424, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 425, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 428, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 431, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 436, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 438, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.044007, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "generic_message", "value": "Starting performance mode", "time_ms": 0.050604, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 841, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.057325, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 0.076335, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "generated_samples_per_query", "value": 10, "time_ms": 0.076335, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 0.076335, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 0.123350, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "issue_query_controller.cc", "line_no": 482, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 8807.518934, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 8807.518934, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 8807.518934, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 8807.518934, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 8807.518934, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 8807.518934, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "power_begin", "value": "09-23-2024 21:01:19.085", "time_ms": 8807.520126, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "power_end", "value": "09-23-2024 21:01:27.888", "time_ms": 8807.520126, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 644, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 649, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 650, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 651, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "early_stopping_result", "value": "", "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 669, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_query_count", "value": 1, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 679, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_samples_per_second", "value": 1.13598, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 735, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_min_latency_ns", "value": 2938941202, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 741, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_max_latency_ns", "value": 8802991466, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 742, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 5291292254, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 743, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 5870358332, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 8802991466, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 8802991466, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 8802991466, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 8802991466, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 156598, "tid": 156598}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 8802991466, "time_ms": 8807.538061, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 156598, "tid": 156598}} diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..f1e79ee --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,51 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 1.13598 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 2938941202 +Max latency (ns) : 8802991466 +Mean latency (ns) : 5291292254 +50.00 percentile latency (ns) : 5870358332 +90.00 percentile latency (ns) : 8802991466 +95.00 percentile latency (ns) : 8802991466 +97.00 percentile latency (ns) : 8802991466 +99.00 percentile latency (ns) : 8802991466 +99.90 percentile latency (ns) : 8802991466 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 10 +target_qps : 0.05 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 10 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 5000 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/accuracy.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/accuracy.txt new file mode 100644 index 0000000..f7bc644 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/accuracy.txt @@ -0,0 +1,2 @@ +Accuracy Results: {'FID_SCORE': 236.8087101317688, 'CLIP_SCORE': 15.586050063371658} +hash=3e0df040b48a1d30350895404d7509ad0beab075a7fdb5aa9252ace6ef8c5922 diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/images/captions.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/images/captions.txt new file mode 100644 index 0000000..102b05d --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/images/captions.txt @@ -0,0 +1,10 @@ +4655 Close up of a red fire hydrant near a sidewalk. +2569 A dark table has a large arrangement of food. +1303 A baby boy standing inside of a wooden crib. +109 People walking toward an airplane to board it. +4509 a couple of horses grazing on some green grass +3009 A horse that is standing with a cart near birds. +2179 A man holds up a Polish sausage on a bun. +1826 Two dogs resting comfortably on a tiled floor. +2094 A cat hiding in a basket of some sort. +3340 Vintage picture of a man and a horse on the farm. diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json new file mode 100644 index 0000000..09fe24b --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json @@ -0,0 +1,7 @@ +[ +{ "seq_id" : 2, "qsl_idx" : 46, "data" : 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} +] diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt new file mode 100644 index 0000000..c6fa787 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt @@ -0,0 +1,68 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.003333, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-09-19T17:52:23.329269", "time_ms": 0.003333, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-09-20T00:52:23.329275", "time_ms": 0.003333, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-02-15T15:46:50-05:00", "time_ms": 0.003333, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "486a629ea4d5c5150f452d0b0a196bf71fd2021e Hotfix: DLRMv2 Audit Test01 fallback failure (#1626)\nf9a643c0a0e920588da1b51a1d822e1071a9dbec Add number of tokens to offline (#1623)\nf06b920eac2170df38b5502c7443f50c9afa6045 Bugfix: equal-issue mode on offline causing accuracy run to fail (3D-UNet) (#1624)\n0ed5190e82e1ca1cf95626e50e61cb6678c7f2ff Fix submission checker and TEST06 for Llama2 (#1616)\n817dd961221d3ca284b024368130bd5dc5e4b54a Turn equal issue mode off for TEST06 (#1615)\n840435a1abe8be823e0a5a18ad3173bc520aa24f Update README.md with CM commands to download stable-diffusion, gptj and dlrmv2 models (#1604)\n3190d09a148bc1d72c9d946e4cf3b54db0d0e60a Typo fix in README.md (#1588)\nb0777f0bd3b7e5cd6a51d670d8b4df656cf6fb29 Update README.md - remove unwanted lines in CM commands (#1601)\nd7dba0826ac96a0e8bcae525086961e47c409a38 Remove loadgen warnings (#1608)\nd45a66c33bb0b6548d6172b38645bf94ffe24b39 Add upper limit to tokens per sample (#1612)\n44285d9a44041c3d4f7df0acf1e72c375e9fcbd2 Set completed samples per second as llama metric (#1613)\n357ccefca4db55ff373e029d5d1e3e6246bde5d4 Enable equal issue mode for LLM benchmarks (#1610)\n104d85531af7ae2a07ded36dd6e8c7f2c7746d06 Add sample length check to test06 (#1603)\n473053fc9f1b8c5edf60e11ec74607126938fbc4 Fix loadgen token metrics latency constrains (#1596)\ncc3daae3c7f18d7eedc5ffbc271d324e5aca6233 #1598: fix token and sample logging for Llama2 when accuracy_log_sampling_target is enabled (#1599)\n3a902e598e5a17013c26fea975c0a60e6d7feae1 Add support to dump 10 compliance images during accuracy run for SDXL (#1591)", "time_ms": 0.003333, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.003333, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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"pid": 161368, "tid": 161368}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 38320.896050, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 38320.896050, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 38320.896050, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 38320.896050, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "power_begin", "value": "09-23-2024 21:04:22.410", "time_ms": 38320.897723, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 161368, "tid": 161368}} +:::MLLOG {"key": "power_end", "value": "09-23-2024 21:05:00.702", "time_ms": 38320.897723, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 161368, "tid": 161368}} diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..d5cc097 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt @@ -0,0 +1,85 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.003730, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-09-19T17:52:23.329269", "time_ms": 0.003730, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-09-20T00:52:23.329275", "time_ms": 0.003730, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-02-15T15:46:50-05:00", "time_ms": 0.003730, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "486a629ea4d5c5150f452d0b0a196bf71fd2021e Hotfix: DLRMv2 Audit Test01 fallback failure (#1626)\nf9a643c0a0e920588da1b51a1d822e1071a9dbec Add number of tokens to offline (#1623)\nf06b920eac2170df38b5502c7443f50c9afa6045 Bugfix: equal-issue mode on offline causing accuracy run to fail (3D-UNet) (#1624)\n0ed5190e82e1ca1cf95626e50e61cb6678c7f2ff Fix submission checker and TEST06 for Llama2 (#1616)\n817dd961221d3ca284b024368130bd5dc5e4b54a Turn equal issue mode off for TEST06 (#1615)\n840435a1abe8be823e0a5a18ad3173bc520aa24f Update README.md with CM commands to download stable-diffusion, gptj and dlrmv2 models (#1604)\n3190d09a148bc1d72c9d946e4cf3b54db0d0e60a Typo fix in README.md (#1588)\nb0777f0bd3b7e5cd6a51d670d8b4df656cf6fb29 Update README.md - remove unwanted lines in CM commands (#1601)\nd7dba0826ac96a0e8bcae525086961e47c409a38 Remove loadgen warnings (#1608)\nd45a66c33bb0b6548d6172b38645bf94ffe24b39 Add upper limit to tokens per sample (#1612)\n44285d9a44041c3d4f7df0acf1e72c375e9fcbd2 Set completed samples per second as llama metric (#1613)\n357ccefca4db55ff373e029d5d1e3e6246bde5d4 Enable equal issue mode for LLM benchmarks (#1610)\n104d85531af7ae2a07ded36dd6e8c7f2c7746d06 Add sample length check to test06 (#1603)\n473053fc9f1b8c5edf60e11ec74607126938fbc4 Fix loadgen token metrics latency constrains (#1596)\ncc3daae3c7f18d7eedc5ffbc271d324e5aca6233 #1598: fix token and sample logging for Llama2 when accuracy_log_sampling_target is enabled (#1599)\n3a902e598e5a17013c26fea975c0a60e6d7feae1 Add support to dump 10 compliance images during accuracy run for SDXL (#1591)", "time_ms": 0.003730, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.003730, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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"file": "test_settings_internal.cc", "line_no": 268, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "requested_test_mode", "value": "PerformanceOnly", "time_ms": 0.044219, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 269, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.044219, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 306, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.044219, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 312, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, 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"line_no": 333, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_scenario", "value": "Offline", "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 409, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_test_mode", "value": "PerformanceOnly", "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 410, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_samples_per_query", "value": 10, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 412, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_target_qps", "value": 0.05, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 413, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 414, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 415, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_max_async_queries", "value": 1, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 417, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_target_duration_ms", "value": 0, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_min_duration_ms", "value": 0, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 420, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_max_duration_ms", "value": 0, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 421, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 422, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_max_query_count", "value": 10, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 423, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_min_sample_count", "value": 10, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 424, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 425, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 428, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 431, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 436, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 438, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.044390, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "generic_message", "value": "Starting performance mode", "time_ms": 0.050846, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 841, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.062304, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 0.079842, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "generated_samples_per_query", "value": 10, "time_ms": 0.079842, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 0.079842, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 0.131911, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "issue_query_controller.cc", "line_no": 482, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 8832.553599, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 8832.553599, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 8832.553599, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 8832.553599, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 8832.553599, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 8832.553599, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "power_begin", "value": "09-23-2024 21:03:39.809", "time_ms": 8832.555834, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "power_end", "value": "09-23-2024 21:03:48.635", "time_ms": 8832.555834, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 644, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 649, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 650, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 651, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "early_stopping_result", "value": "", "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 669, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_query_count", "value": 1, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 679, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_samples_per_second", "value": 1.13292, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 735, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_min_latency_ns", "value": 2938170548, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 741, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_max_latency_ns", "value": 8826755187, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 742, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 5295562011, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 743, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 5881030207, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 8826755187, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 8826755187, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 8826755187, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 8826755187, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 159986, "tid": 159986}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 8826755187, "time_ms": 8832.584527, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 159986, "tid": 159986}} diff --git a/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..3e6a326 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,51 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 1.13292 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 2938170548 +Max latency (ns) : 8826755187 +Mean latency (ns) : 5295562011 +50.00 percentile latency (ns) : 5881030207 +90.00 percentile latency (ns) : 8826755187 +95.00 percentile latency (ns) : 8826755187 +97.00 percentile latency (ns) : 8826755187 +99.00 percentile latency (ns) : 8826755187 +99.90 percentile latency (ns) : 8826755187 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 10 +target_qps : 0.05 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 10 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 5000 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt new file mode 100644 index 0000000..b6c982b --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt @@ -0,0 +1,2 @@ +Accuracy Results: {'FID_SCORE': 238.78369342212613, 'CLIP_SCORE': 15.236237794160843} +hash=44c17777d28c9c97e203b2557506a97eb7787a8b66bc93144dca01b312def56c diff --git a/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/images/captions.txt b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/images/captions.txt new file mode 100644 index 0000000..102b05d --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/images/captions.txt @@ -0,0 +1,10 @@ +4655 Close up of a red fire hydrant near a sidewalk. +2569 A dark table has a large arrangement of food. +1303 A baby boy standing inside of a wooden crib. +109 People walking toward an airplane to board it. +4509 a couple of horses grazing on some green grass +3009 A horse that is standing with a cart near birds. +2179 A man holds up a Polish sausage on a bun. +1826 Two dogs resting comfortably on a tiled floor. +2094 A cat hiding in a basket of some sort. +3340 Vintage picture of a man and a horse on the farm. diff --git a/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json new file mode 100644 index 0000000..36b3f32 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json @@ -0,0 +1,7 @@ +[ +{ "seq_id" : 0, "qsl_idx" : 25, "data" : 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} +] diff --git a/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt new file mode 100644 index 0000000..88e4e25 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt @@ -0,0 +1,70 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.1 @ NA", "time_ms": 0.002340, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 8536, "tid": 8536}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-09-20T11:41:28.772701", "time_ms": 0.002340, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": 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"namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 8536, "tid": 8536}} diff --git a/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..c529000 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt @@ -0,0 +1,87 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.1 @ NA", "time_ms": 0.004452, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-09-20T11:41:28.772701", "time_ms": 0.004452, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-09-20T18:41:28.772706", "time_ms": 0.004452, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "NA", "time_ms": 0.004452, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "NA", "time_ms": 0.004452, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "NA", "time_ms": 0.004452, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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"time_ms": 0.004452, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 67, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "test_datetime", "value": "2024-09-24T07:17:47Z", "time_ms": 0.017477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1198, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "sut_name", "value": "PySUT", "time_ms": 0.017477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1199, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "get_sut_name_duration_ns", "value": 373, "time_ms": 0.017477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1200, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.017477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 50, "time_ms": 0.017477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.017477, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 270, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_test_mode", "value": "PerformanceOnly", "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 271, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 308, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 314, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 315, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_min_query_count", "value": 10, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_max_query_count", "value": 10, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 318, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 319, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 321, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_accuracy_log_rng_seed", "value": 0, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 322, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_accuracy_log_probability", "value": 0, 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"file": "test_settings_internal.cc", "line_no": 329, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "requested_performance_sample_count_override", "value": 5000, "time_ms": 0.020560, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": 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{"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 416, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_target_qps", "value": 0.05, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 417, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 419, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": 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"is_warning": false, "file": "test_settings_internal.cc", "line_no": 425, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_max_query_count", "value": 10, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 427, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_min_sample_count", "value": 10, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 428, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 430, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 432, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 437, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 439, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 444, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 446, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.020675, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 448, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "generic_message", "value": "Starting performance mode", "time_ms": 0.025083, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 841, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.031080, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 2.358641, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "generated_samples_per_query", "value": 10, "time_ms": 2.358641, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 2.358641, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 13508.770770, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "issue_query_controller.cc", "line_no": 482, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 26774.349087, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 26774.349087, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 26774.349087, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 26774.349087, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 26774.349087, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 26774.349087, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "power_begin", "value": "09-24-2024 14:17:47.523", "time_ms": 26774.351142, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "power_end", "value": "09-24-2024 14:18:14.287", "time_ms": 26774.351142, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 655, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 660, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 661, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 662, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "early_stopping_result", "value": "", "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 682, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_query_count", "value": 1, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 692, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_samples_per_second", "value": 0.373636, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 748, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_min_latency_ns", "value": 2917908339, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 754, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_max_latency_ns", "value": 26764022878, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 755, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 14835115692, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 756, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 16158267752, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 26764022878, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 26764022878, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 26764022878, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 26764022878, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 7565, "tid": 7565}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 26764022878, "time_ms": 26774.487157, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 7565, "tid": 7565}} diff --git a/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..16ff2f9 --- /dev/null +++ b/open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,51 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 0.373636 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 2917908339 +Max latency (ns) : 26764022878 +Mean latency (ns) : 14835115692 +50.00 percentile latency (ns) : 16158267752 +90.00 percentile latency (ns) : 26764022878 +95.00 percentile latency (ns) : 26764022878 +97.00 percentile latency (ns) : 26764022878 +99.00 percentile latency (ns) : 26764022878 +99.90 percentile latency (ns) : 26764022878 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 10 +target_qps : 0.05 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 10 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 5000 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt new file mode 100644 index 0000000..06f0305 --- /dev/null +++ b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt @@ -0,0 +1,2 @@ +Accuracy Results: {'FID_SCORE': 233.28573789198563, 'CLIP_SCORE': 15.617164582014084} +hash=953202706713ef563f617835ae760b4dfd306a97ae2c69e96d2ab92de82354c3 diff --git a/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/images/captions.txt b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/images/captions.txt new file mode 100644 index 0000000..102b05d --- /dev/null +++ b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/images/captions.txt @@ -0,0 +1,10 @@ +4655 Close up of a red fire hydrant near a sidewalk. +2569 A dark table has a large arrangement of food. +1303 A baby boy standing inside of a wooden crib. +109 People walking toward an airplane to board it. +4509 a couple of horses grazing on some green grass +3009 A horse that is standing with a cart near birds. +2179 A man holds up a Polish sausage on a bun. +1826 Two dogs resting comfortably on a tiled floor. +2094 A cat hiding in a basket of some sort. +3340 Vintage picture of a man and a horse on the farm. diff --git a/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json new file mode 100644 index 0000000..55b7073 --- /dev/null +++ b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json @@ -0,0 +1,7 @@ +[ +{ "seq_id" : 0, "qsl_idx" : 25, "data" : 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} +] diff --git a/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt new file mode 100644 index 0000000..1d73e46 --- /dev/null +++ b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt @@ -0,0 +1,68 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.003990, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-10-03T02:56:09.443291", "time_ms": 0.003990, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-10-03T09:56:09.443297", "time_ms": 0.003990, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-02-15T15:46:50-05:00", "time_ms": 0.003990, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "486a629ea4d5c5150f452d0b0a196bf71fd2021e Hotfix: DLRMv2 Audit Test01 fallback failure (#1626)\nf9a643c0a0e920588da1b51a1d822e1071a9dbec Add number of tokens to offline (#1623)\nf06b920eac2170df38b5502c7443f50c9afa6045 Bugfix: equal-issue mode on offline causing accuracy run to fail (3D-UNet) (#1624)\n0ed5190e82e1ca1cf95626e50e61cb6678c7f2ff Fix submission checker and TEST06 for Llama2 (#1616)\n817dd961221d3ca284b024368130bd5dc5e4b54a Turn equal issue mode off for TEST06 (#1615)\n840435a1abe8be823e0a5a18ad3173bc520aa24f Update README.md with CM commands to download stable-diffusion, gptj and dlrmv2 models (#1604)\n3190d09a148bc1d72c9d946e4cf3b54db0d0e60a Typo fix in README.md (#1588)\nb0777f0bd3b7e5cd6a51d670d8b4df656cf6fb29 Update README.md - remove unwanted lines in CM commands (#1601)\nd7dba0826ac96a0e8bcae525086961e47c409a38 Remove loadgen warnings (#1608)\nd45a66c33bb0b6548d6172b38645bf94ffe24b39 Add upper limit to tokens per sample (#1612)\n44285d9a44041c3d4f7df0acf1e72c375e9fcbd2 Set completed samples per second as llama metric (#1613)\n357ccefca4db55ff373e029d5d1e3e6246bde5d4 Enable equal issue mode for LLM benchmarks (#1610)\n104d85531af7ae2a07ded36dd6e8c7f2c7746d06 Add sample length check to test06 (#1603)\n473053fc9f1b8c5edf60e11ec74607126938fbc4 Fix loadgen token metrics latency constrains (#1596)\ncc3daae3c7f18d7eedc5ffbc271d324e5aca6233 #1598: fix token and sample logging for Llama2 when accuracy_log_sampling_target is enabled (#1599)\n3a902e598e5a17013c26fea975c0a60e6d7feae1 Add support to dump 10 compliance images during accuracy run for SDXL (#1591)", "time_ms": 0.003990, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.003990, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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"logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 38322.596489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 38322.596489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 38322.596489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 38322.596489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "power_begin", "value": "10-06-2024 03:28:13.729", "time_ms": 38322.598465, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 36745, "tid": 36745}} +:::MLLOG {"key": "power_end", "value": "10-06-2024 03:28:52.031", "time_ms": 38322.598465, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 36745, "tid": 36745}} diff --git a/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..4cdb14f --- /dev/null +++ b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt @@ -0,0 +1,85 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.0 @ 486a629ea4", "time_ms": 0.003241, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-10-03T02:56:09.443291", "time_ms": 0.003241, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-10-03T09:56:09.443297", "time_ms": 0.003241, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-02-15T15:46:50-05:00", "time_ms": 0.003241, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "486a629ea4d5c5150f452d0b0a196bf71fd2021e Hotfix: DLRMv2 Audit Test01 fallback failure (#1626)\nf9a643c0a0e920588da1b51a1d822e1071a9dbec Add number of tokens to offline (#1623)\nf06b920eac2170df38b5502c7443f50c9afa6045 Bugfix: equal-issue mode on offline causing accuracy run to fail (3D-UNet) (#1624)\n0ed5190e82e1ca1cf95626e50e61cb6678c7f2ff Fix submission checker and TEST06 for Llama2 (#1616)\n817dd961221d3ca284b024368130bd5dc5e4b54a Turn equal issue mode off for TEST06 (#1615)\n840435a1abe8be823e0a5a18ad3173bc520aa24f Update README.md with CM commands to download stable-diffusion, gptj and dlrmv2 models (#1604)\n3190d09a148bc1d72c9d946e4cf3b54db0d0e60a Typo fix in README.md (#1588)\nb0777f0bd3b7e5cd6a51d670d8b4df656cf6fb29 Update README.md - remove unwanted lines in CM commands (#1601)\nd7dba0826ac96a0e8bcae525086961e47c409a38 Remove loadgen warnings (#1608)\nd45a66c33bb0b6548d6172b38645bf94ffe24b39 Add upper limit to tokens per sample (#1612)\n44285d9a44041c3d4f7df0acf1e72c375e9fcbd2 Set completed samples per second as llama metric (#1613)\n357ccefca4db55ff373e029d5d1e3e6246bde5d4 Enable equal issue mode for LLM benchmarks (#1610)\n104d85531af7ae2a07ded36dd6e8c7f2c7746d06 Add sample length check to test06 (#1603)\n473053fc9f1b8c5edf60e11ec74607126938fbc4 Fix loadgen token metrics latency constrains (#1596)\ncc3daae3c7f18d7eedc5ffbc271d324e5aca6233 #1598: fix token and sample logging for Llama2 when accuracy_log_sampling_target is enabled (#1599)\n3a902e598e5a17013c26fea975c0a60e6d7feae1 Add support to dump 10 compliance images during accuracy run for SDXL (#1591)", "time_ms": 0.003241, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.003241, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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+:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.040521, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 50, "time_ms": 0.040521, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.040521, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.046069, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 268, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "requested_test_mode", "value": "PerformanceOnly", "time_ms": 0.046069, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 269, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.046069, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 306, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.046069, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 312, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 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"POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 413, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 414, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 415, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_max_async_queries", "value": 1, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 417, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_target_duration_ms", "value": 0, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_min_duration_ms", "value": 0, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 420, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_max_duration_ms", "value": 0, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 421, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 422, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_max_query_count", "value": 10, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 423, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_min_sample_count", "value": 10, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 424, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 425, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 428, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 431, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 436, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 438, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.046242, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "generic_message", "value": "Starting performance mode", "time_ms": 0.051550, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 841, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.058629, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 0.080429, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "generated_samples_per_query", "value": 10, "time_ms": 0.080429, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 0.080429, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 0.129812, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "issue_query_controller.cc", "line_no": 482, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 8817.340568, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 8817.340568, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 8817.340568, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 8817.340568, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 8817.340568, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 8817.340568, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "power_begin", "value": "10-06-2024 03:27:30.691", "time_ms": 8817.342483, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "power_end", "value": "10-06-2024 03:27:39.500", "time_ms": 8817.342483, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 644, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 649, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 650, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 651, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "early_stopping_result", "value": "", "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 669, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_query_count", "value": 1, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 679, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_samples_per_second", "value": 1.13521, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 735, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_min_latency_ns", "value": 2939659114, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 741, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_max_latency_ns", "value": 8808958712, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 742, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 5289087830, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 743, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 5873224599, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 8808958712, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 8808958712, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 8808958712, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 8808958712, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 35312, "tid": 35312}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 8808958712, "time_ms": 8817.367977, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 745, "pid": 35312, "tid": 35312}} diff --git a/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..f96f98b --- /dev/null +++ b/open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,51 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 1.13521 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 2939659114 +Max latency (ns) : 8808958712 +Mean latency (ns) : 5289087830 +50.00 percentile latency (ns) : 5873224599 +90.00 percentile latency (ns) : 8808958712 +95.00 percentile latency (ns) : 8808958712 +97.00 percentile latency (ns) : 8808958712 +99.00 percentile latency (ns) : 8808958712 +99.90 percentile latency (ns) : 8808958712 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 10 +target_qps : 0.05 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 10 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 5000 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt new file mode 100644 index 0000000..61867ab --- /dev/null +++ b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/accuracy.txt @@ -0,0 +1,2 @@ +Accuracy Results: {'FID_SCORE': 235.69504308101006, 'CLIP_SCORE': 15.18544016778469} 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} +] diff --git a/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt new file mode 100644 index 0000000..ccee353 --- /dev/null +++ b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt @@ -0,0 +1,70 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.1 @ c4d0b3ea98", "time_ms": 0.003861, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-10-01T11:57:27.139962", "time_ms": 0.003861, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-10-01T11:57:27.139968", "time_ms": 0.003861, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-09-24T11:39:18-05:00", "time_ms": 0.003861, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "c4d0b3ea98e6fe7252e50cb573f0d523da7979df Update docs: SCC24, fix broken redirect (#1843)\n7d2f0c41e5cd79c9178702867392e38f57953338 Update DLRM readme (#1811)\ncf5fddc5d0746bf3820eb0ab7294bbf709d788ab Enable systems to be marked as power only (#1850)\n81c2de69de4af90410cd1ba000fc5bd731bf6dee Documentation updates (#1821)\n73b02798219c794a735a7f2ddabbc3df9173352d Fix error with generate_final_report.py when the input CSV file is empty (#1827)", "time_ms": 0.003861, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.003861, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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"time_ms": 0.003861, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 67, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "test_datetime", "value": "2024-10-01T12:23:47Z", "time_ms": 0.011746, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1198, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "sut_name", "value": "PySUT", "time_ms": 0.011746, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1199, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "get_sut_name_duration_ns", "value": 237, "time_ms": 0.011746, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1200, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.011746, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 50, "time_ms": 0.011746, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.011746, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 270, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_test_mode", "value": "AccuracyOnly", "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 271, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 308, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 314, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 315, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_min_query_count", "value": 50, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_max_query_count", "value": 50, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 318, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 319, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 321, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_accuracy_log_rng_seed", "value": 0, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 322, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": 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"metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 329, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "requested_performance_sample_count_override", "value": 5000, "time_ms": 0.014837, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 15677, 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"namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 446, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.015970, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 448, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "generic_message", "value": "Starting accuracy mode", "time_ms": 0.019992, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1090, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.029828, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 2.054372, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "generated_samples_per_query", "value": 50, "time_ms": 2.054372, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 2.054372, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 132563.266575, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 132563.266575, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 132563.266575, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 132563.266575, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 132563.266575, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 132563.266575, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "power_begin", "value": "10-01-2024 12:23:47.611", "time_ms": 132563.269351, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 15677, "tid": 15677}} +:::MLLOG {"key": "power_end", "value": "10-01-2024 12:26:00.161", "time_ms": 132563.269351, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 15677, "tid": 15677}} diff --git a/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..eef0fec --- /dev/null +++ b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt @@ -0,0 +1,87 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.1 @ c4d0b3ea98", "time_ms": 0.002987, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-10-01T11:57:27.139962", "time_ms": 0.002987, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-10-01T11:57:27.139968", "time_ms": 0.002987, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-09-24T11:39:18-05:00", "time_ms": 0.002987, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "c4d0b3ea98e6fe7252e50cb573f0d523da7979df Update docs: SCC24, fix broken redirect (#1843)\n7d2f0c41e5cd79c9178702867392e38f57953338 Update DLRM readme (#1811)\ncf5fddc5d0746bf3820eb0ab7294bbf709d788ab Enable systems to be marked as power only (#1850)\n81c2de69de4af90410cd1ba000fc5bd731bf6dee Documentation updates (#1821)\n73b02798219c794a735a7f2ddabbc3df9173352d Fix error with generate_final_report.py when the input CSV file is empty (#1827)", "time_ms": 0.002987, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.002987, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "loadgen_file_sha1", "value": {"/.clang-format":"012aad77e5206c89d50718c46c119d1f3cb056b2","/CMakeLists.txt":"d5274ff0b56e8d3cdb273174628a4461fca6f02a","/README.md":"20a55bb946c2c0bbb564ced2af1e48efd096b3a8","/README_BUILD.md":"5f6c6a784e9cd6995db47f9b9f70b1769909c9d8","/README_FAQ.md":"01f9ae9887f50bc030dc6107e740f40c43ca388f","/bindings/c_api.cc":"32181da9e161c285f8fe46ddaa49e6cba2f9f918","/bindings/c_api.h":"91f58bd79b83b278f3240174a9af747fc38aff74","/bindings/python_api.cc":"03b4324871396dad386ac67535dbc893b098ba2f","/diagram_network_submission.png":"53dba8ad4272190ceb6335c12fd25e53dc02a8cb","/diagram_submission.png":"84c2f79309b237cef652aef6a187ba8e875a3952","/early_stopping.cc":"0cd7b546a389deac73f7955cd39255ed76557d62","/early_stopping.h":"158fcae6a5f47e82150d6416fa1f7bcef37e77fe","/issue_query_controller.cc":"126e952d00f4ea9efd12405fb209aa3ed585e4b2","/issue_query_controller.h":"923d9d5cdf598e3ec33d7a1110a31f7e11527ec7","/loadgen.cc":"6650091ba7a918f343b06eb7a5aa540eae87275f","/loadgen.h":"e00fdc6dbc85a8c9a8485dbcbfe2944f81251c4e","/loadgen_integration_diagram.svg":"47f748307536f80cfc606947b440dd732afc2637","/logging.cc":"197efc96d178e5d33a750d07fa7b2966417506ea","/logging.h":"ddb961df7bcc145bcd7cce8c21f7cf075350dcbe","/pyproject.toml":"ca17720f9c8246e821331946d893e830fc88f8bd","/query_dispatch_library.h":"13ad6d842200cb161d6927eb74a3fafd79c46c75","/query_sample.h":"e9187c8612bbdc972305b789feb6e15c26e96cfe","/query_sample_library.h":"8323a2225be1dff31f08ecc86b76eb3de06568bc","/requirements.txt":"a5ff7e77caa6e9e22ada90f0de0c865c987bf167","/results.cc":"34e2d2a44324cb07c884f92146ecbb8ef9d704e2","/results.h":"d82500c326c2de83db411f1146882aa4692b419c","/setup.py":"13c49b028b22749b5f3c44f3d9bb489e8c0574e9","/system_under_test.h":"18d4809589dae33317d88d9beeb5491a6e1ccdec","/test_settings.h":"c15c3e150030089a8d634bd2ad6d4b644002e613","/test_settings_internal.cc":"6fb859a8675d2f3ec9f8f124ec880e30f68cfbe6","/test_settings_internal.h":"f1d5335b53ca610c30e0edc5d07999a27b5b4b9a","/utils.cc":"3df8fdabf6eaea4697cf25d1dcb89cae88e36efd","/utils.h":"40775e32d619ea6356826ae5ea4174c7911f6894","/version.cc":"cbec2a5f98f9786c8c3d8b06b3d12df0b6550fa0","/version.h":"9d574baa64424e9c708fcfedd3dbb0b518a65fcc","/version_generator.py":"eea9b9cb1a06cd1abe1bbdaee82f9af31527fedb"}, "time_ms": 0.002987, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 67, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "test_datetime", "value": "2024-10-01T12:22:52Z", "time_ms": 0.013417, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1198, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "sut_name", "value": "PySUT", "time_ms": 0.013417, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1199, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "get_sut_name_duration_ns", "value": 168, "time_ms": 0.013417, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1200, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.013417, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 50, "time_ms": 0.013417, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.013417, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 270, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_test_mode", "value": "PerformanceOnly", "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 271, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 308, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 314, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 315, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_min_query_count", "value": 10, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_max_query_count", "value": 10, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 318, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 319, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 321, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_accuracy_log_rng_seed", "value": 0, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 322, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_accuracy_log_probability", "value": 0, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 324, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_accuracy_log_sampling_target", "value": 0, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 326, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_print_timestamps", "value": false, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 328, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_performance_issue_unique", "value": false, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 329, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_performance_sample_count_override", "value": 5000, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "requested_sample_concatenate_permutation", "value": false, "time_ms": 0.016294, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 337, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_scenario", "value": "Offline", "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 413, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_test_mode", "value": "PerformanceOnly", "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 414, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_samples_per_query", "value": 10, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 416, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_target_qps", "value": 0.05, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 417, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 419, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_max_async_queries", "value": 1, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 421, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_target_duration_ms", "value": 0, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 422, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_min_duration_ms", "value": 0, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 424, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_max_duration_ms", "value": 0, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 425, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_max_query_count", "value": 10, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 427, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_min_sample_count", "value": 10, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 428, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 430, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 432, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 437, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 439, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 444, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 446, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.016392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 448, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "generic_message", "value": "Starting performance mode", "time_ms": 0.021168, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 841, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.030456, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 1.961914, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "generated_samples_per_query", "value": 10, "time_ms": 1.961914, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 1.961914, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 13377.264816, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "issue_query_controller.cc", "line_no": 482, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 26540.206092, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 26540.206092, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 26540.206092, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 26540.206092, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 26540.206092, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 26540.206092, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "power_begin", "value": "10-01-2024 12:22:52.603", "time_ms": 26540.208934, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "power_end", "value": "10-01-2024 12:23:19.132", "time_ms": 26540.208934, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 655, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 660, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 661, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 662, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "early_stopping_result", "value": "", "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 682, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_query_count", "value": 1, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 692, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_samples_per_second", "value": 0.376944, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 748, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_min_latency_ns", "value": 2883519461, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 754, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_max_latency_ns", "value": 26529139726, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 755, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 14697904196, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 756, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 16002968321, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 26529139726, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 26529139726, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 26529139726, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 26529139726, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 12736, "tid": 12736}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 26529139726, "time_ms": 26540.307750, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 12736, "tid": 12736}} diff --git a/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..8deeb4e --- /dev/null +++ b/open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,51 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 0.376944 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 2883519461 +Max latency (ns) : 26529139726 +Mean latency (ns) : 14697904196 +50.00 percentile latency (ns) : 16002968321 +90.00 percentile latency (ns) : 26529139726 +95.00 percentile latency (ns) : 26529139726 +97.00 percentile latency (ns) : 26529139726 +99.00 percentile latency (ns) : 26529139726 +99.90 percentile latency (ns) : 26529139726 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 10 +target_qps : 0.05 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 10 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 5000 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/accuracy.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/accuracy.txt new file mode 100644 index 0000000..bf69ed4 --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/accuracy.txt @@ -0,0 +1,8 @@ +Constructing QSL +Encoding Samples + +Results + +{'rouge1': np.float64(32.2581), 'rouge2': np.float64(6.6667), 'rougeL': np.float64(22.5806), 'rougeLsum': np.float64(25.8065), 'gen_len': np.int64(258), 'gen_num': 1} +Finished destroying QSL. +hash=5470ad247d575ae6dd919dbaec13f5d488c15366f13a7dc52cb0e73e062cc958 diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/mlperf_log_accuracy.json new file mode 100644 index 0000000..0679df2 --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/mlperf_log_accuracy.json @@ -0,0 +1,3 @@ +[ +{ "seq_id" : 0, "qsl_idx" : 0, "data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} +] diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/mlperf_log_detail.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/mlperf_log_detail.txt new file mode 100644 index 0000000..85849f1 --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/mlperf_log_detail.txt @@ -0,0 +1,70 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.1 @ c4d0b3ea98", "time_ms": 0.010392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-09-25T21:34:25.672588", "time_ms": 0.010392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-09-25T21:34:25.672594", "time_ms": 0.010392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-09-24T11:39:18-05:00", "time_ms": 0.010392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "c4d0b3ea98e6fe7252e50cb573f0d523da7979df Update docs: SCC24, fix broken redirect (#1843)\n7d2f0c41e5cd79c9178702867392e38f57953338 Update DLRM readme (#1811)\ncf5fddc5d0746bf3820eb0ab7294bbf709d788ab Enable systems to be marked as power only (#1850)\n81c2de69de4af90410cd1ba000fc5bd731bf6dee Documentation updates (#1821)\n73b02798219c794a735a7f2ddabbc3df9173352d Fix error with generate_final_report.py when the input CSV file is empty (#1827)", "time_ms": 0.010392, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 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{"key": "qsl_name", "value": "PyQSL", "time_ms": 0.016165, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 1, "time_ms": 0.016165, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 1, "time_ms": 0.016165, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 270, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_test_mode", "value": "AccuracyOnly", "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 271, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 1, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 308, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 314, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 315, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_min_query_count", "value": 1, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_max_query_count", "value": 1, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 318, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 319, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 321, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_accuracy_log_rng_seed", "value": 0, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 322, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_accuracy_log_probability", "value": 0, 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"file": "test_settings_internal.cc", "line_no": 329, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "requested_performance_sample_count_override", "value": 13368, "time_ms": 0.022222, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": 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"generated_query_count", "value": 1, "time_ms": 0.047865, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "generated_samples_per_query", "value": 1, "time_ms": 0.047865, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "generated_query_duration", "value": 1000000000, "time_ms": 0.047865, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 1349.243489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 1349.243489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 1349.243489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 1349.243489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 1349.243489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 1349.243489, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "power_begin", "value": "09-25-2024 21:38:18.654", "time_ms": 1349.244339, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 6139, "tid": 6139}} +:::MLLOG {"key": "power_end", "value": "09-25-2024 21:38:20.002", "time_ms": 1349.244339, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 6139, "tid": 6139}} diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/mlperf_log_summary.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/performance/run_1/mlperf_log_accuracy.json b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/performance/run_1/mlperf_log_detail.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..635c612 --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/performance/run_1/mlperf_log_detail.txt @@ -0,0 +1,88 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.1 @ c4d0b3ea98", "time_ms": 0.005318, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-09-25T21:34:25.672588", "time_ms": 0.005318, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-09-25T21:34:25.672594", "time_ms": 0.005318, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-09-24T11:39:18-05:00", "time_ms": 0.005318, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "c4d0b3ea98e6fe7252e50cb573f0d523da7979df Update docs: SCC24, fix broken redirect (#1843)\n7d2f0c41e5cd79c9178702867392e38f57953338 Update DLRM readme (#1811)\ncf5fddc5d0746bf3820eb0ab7294bbf709d788ab Enable systems to be marked as power only (#1850)\n81c2de69de4af90410cd1ba000fc5bd731bf6dee Documentation updates (#1821)\n73b02798219c794a735a7f2ddabbc3df9173352d Fix error with generate_final_report.py when the input CSV file is empty (#1827)", "time_ms": 0.005318, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.005318, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "loadgen_file_sha1", "value": 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"time_ms": 0.005318, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 67, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "test_datetime", "value": "2024-09-25T21:37:28Z", "time_ms": 0.010962, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1198, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "sut_name", "value": "PySUT", "time_ms": 0.010962, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1199, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "get_sut_name_duration_ns", "value": 153, "time_ms": 0.010962, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1200, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.010962, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 1, "time_ms": 0.010962, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 1, "time_ms": 0.010962, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 270, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_test_mode", "value": "PerformanceOnly", "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 271, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 1, "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 308, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 314, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 315, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_min_query_count", "value": 1, "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_max_query_count", "value": 1, "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", 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"file": "test_settings_internal.cc", "line_no": 329, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "requested_performance_sample_count_override", "value": 13368, "time_ms": 0.027859, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": 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{"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 416, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_target_qps", "value": 1, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 417, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 419, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_max_async_queries", "value": 1, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 421, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_target_duration_ms", "value": 0, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 422, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_min_duration_ms", "value": 0, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 424, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_max_duration_ms", "value": 0, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 425, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_max_query_count", "value": 1, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 427, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_min_sample_count", "value": 1, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 428, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 430, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 432, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 437, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 439, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 444, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 13368, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 446, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.028193, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 448, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "generic_message", "value": "Starting performance mode", "time_ms": 0.030257, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 841, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "loaded_qsl_set", "value": [0], "time_ms": 0.033907, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 0.057329, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "generated_samples_per_query", "value": 1, "time_ms": 0.057329, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "generated_query_duration", "value": 1000000000, "time_ms": 0.057329, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 1303.440918, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "issue_query_controller.cc", "line_no": 482, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 1333.551056, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 1333.551056, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 1333.551056, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 1333.551056, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 1333.551056, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 1333.551056, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "power_begin", "value": "09-25-2024 21:37:28.228", "time_ms": 1333.552456, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "power_end", "value": "09-25-2024 21:37:29.531", "time_ms": 1333.552456, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 655, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 660, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 661, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 662, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "early_stopping_result", "value": "", "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 682, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_query_count", "value": 1, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 692, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_samples_per_second", "value": 0.767359, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 748, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_min_latency_ns", "value": 1303171107, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 754, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_max_latency_ns", "value": 1303171107, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 755, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 1303171107, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 756, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 1303171107, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 1303171107, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 1303171107, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 1303171107, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 1303171107, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 1303171107, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2804, "tid": 2804}} +:::MLLOG {"key": "result_inferred_tokens_per_second", "value": 52.9478, "time_ms": 1333.567407, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 806, "pid": 2804, "tid": 2804}} diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..82a86ea --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,52 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 0.767359 +Tokens per second (inferred): 52.9478 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 1303171107 +Max latency (ns) : 1303171107 +Mean latency (ns) : 1303171107 +50.00 percentile latency (ns) : 1303171107 +90.00 percentile latency (ns) : 1303171107 +95.00 percentile latency (ns) : 1303171107 +97.00 percentile latency (ns) : 1303171107 +99.00 percentile latency (ns) : 1303171107 +99.90 percentile latency (ns) : 1303171107 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 1 +target_qps : 1 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 1 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 13368 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/accuracy.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/accuracy.txt new file mode 100644 index 0000000..61867ab --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/accuracy.txt @@ -0,0 +1,2 @@ +Accuracy Results: {'FID_SCORE': 235.69504308101006, 'CLIP_SCORE': 15.18544016778469} +hash=52ff0ab803fb8e84330e530a1f73ff0ab9a07e7715792ead5a5a76c9d533dd3e diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/images/captions.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/images/captions.txt new file mode 100644 index 0000000..102b05d --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/images/captions.txt @@ -0,0 +1,10 @@ +4655 Close up of a red fire hydrant near a sidewalk. +2569 A dark table has a large arrangement of food. +1303 A baby boy standing inside of a wooden crib. +109 People walking toward an airplane to board it. +4509 a couple of horses grazing on some green grass +3009 A horse that is standing with a cart near birds. +2179 A man holds up a Polish sausage on a bun. +1826 Two dogs resting comfortably on a tiled floor. +2094 A cat hiding in a basket of some sort. +3340 Vintage picture of a man and a horse on the farm. diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json new file mode 100644 index 0000000..45ce178 --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json @@ -0,0 +1,7 @@ +[ +{ "seq_id" : 0, "qsl_idx" : 25, "data" : 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"namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 6307, "tid": 6307}} diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..6abacae --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt @@ -0,0 +1,87 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.1 @ c4d0b3ea98", "time_ms": 0.003035, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-09-26T04:48:25.151989", "time_ms": 0.003035, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-09-26T04:48:25.151997", "time_ms": 0.003035, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-09-24T11:39:18-05:00", "time_ms": 0.003035, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "c4d0b3ea98e6fe7252e50cb573f0d523da7979df Update docs: SCC24, fix broken redirect (#1843)\n7d2f0c41e5cd79c9178702867392e38f57953338 Update DLRM readme (#1811)\ncf5fddc5d0746bf3820eb0ab7294bbf709d788ab Enable systems to be marked as power only (#1850)\n81c2de69de4af90410cd1ba000fc5bd731bf6dee Documentation updates (#1821)\n73b02798219c794a735a7f2ddabbc3df9173352d Fix error with generate_final_report.py when the input CSV file is empty (#1827)", "time_ms": 0.003035, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.003035, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "loadgen_file_sha1", "value": {"/.clang-format":"012aad77e5206c89d50718c46c119d1f3cb056b2","/CMakeLists.txt":"d5274ff0b56e8d3cdb273174628a4461fca6f02a","/README.md":"20a55bb946c2c0bbb564ced2af1e48efd096b3a8","/README_BUILD.md":"5f6c6a784e9cd6995db47f9b9f70b1769909c9d8","/README_FAQ.md":"01f9ae9887f50bc030dc6107e740f40c43ca388f","/bindings/c_api.cc":"32181da9e161c285f8fe46ddaa49e6cba2f9f918","/bindings/c_api.h":"91f58bd79b83b278f3240174a9af747fc38aff74","/bindings/python_api.cc":"03b4324871396dad386ac67535dbc893b098ba2f","/diagram_network_submission.png":"53dba8ad4272190ceb6335c12fd25e53dc02a8cb","/diagram_submission.png":"84c2f79309b237cef652aef6a187ba8e875a3952","/early_stopping.cc":"0cd7b546a389deac73f7955cd39255ed76557d62","/early_stopping.h":"158fcae6a5f47e82150d6416fa1f7bcef37e77fe","/issue_query_controller.cc":"126e952d00f4ea9efd12405fb209aa3ed585e4b2","/issue_query_controller.h":"923d9d5cdf598e3ec33d7a1110a31f7e11527ec7","/loadgen.cc":"6650091ba7a918f343b06eb7a5aa540eae87275f","/loadgen.h":"e00fdc6dbc85a8c9a8485dbcbfe2944f81251c4e","/loadgen_integration_diagram.svg":"47f748307536f80cfc606947b440dd732afc2637","/logging.cc":"197efc96d178e5d33a750d07fa7b2966417506ea","/logging.h":"ddb961df7bcc145bcd7cce8c21f7cf075350dcbe","/pyproject.toml":"ca17720f9c8246e821331946d893e830fc88f8bd","/query_dispatch_library.h":"13ad6d842200cb161d6927eb74a3fafd79c46c75","/query_sample.h":"e9187c8612bbdc972305b789feb6e15c26e96cfe","/query_sample_library.h":"8323a2225be1dff31f08ecc86b76eb3de06568bc","/requirements.txt":"a5ff7e77caa6e9e22ada90f0de0c865c987bf167","/results.cc":"34e2d2a44324cb07c884f92146ecbb8ef9d704e2","/results.h":"d82500c326c2de83db411f1146882aa4692b419c","/setup.py":"13c49b028b22749b5f3c44f3d9bb489e8c0574e9","/system_under_test.h":"18d4809589dae33317d88d9beeb5491a6e1ccdec","/test_settings.h":"c15c3e150030089a8d634bd2ad6d4b644002e613","/test_settings_internal.cc":"6fb859a8675d2f3ec9f8f124ec880e30f68cfbe6","/test_settings_internal.h":"f1d5335b53ca610c30e0edc5d07999a27b5b4b9a","/utils.cc":"3df8fdabf6eaea4697cf25d1dcb89cae88e36efd","/utils.h":"40775e32d619ea6356826ae5ea4174c7911f6894","/version.cc":"cbec2a5f98f9786c8c3d8b06b3d12df0b6550fa0","/version.h":"9d574baa64424e9c708fcfedd3dbb0b518a65fcc","/version_generator.py":"eea9b9cb1a06cd1abe1bbdaee82f9af31527fedb"}, "time_ms": 0.003035, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 67, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "test_datetime", "value": "2024-09-26T04:52:48Z", "time_ms": 0.007044, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1198, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "sut_name", "value": "PySUT", "time_ms": 0.007044, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1199, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "get_sut_name_duration_ns", "value": 204, "time_ms": 0.007044, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1200, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.007044, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 50, "time_ms": 0.007044, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.007044, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 270, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_test_mode", "value": "PerformanceOnly", "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 271, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 308, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 314, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 315, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_min_query_count", "value": 1, "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_max_query_count", "value": 1, "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", 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"file": "test_settings_internal.cc", "line_no": 329, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "requested_performance_sample_count_override", "value": 5000, "time_ms": 0.010020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": 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{"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 416, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_target_qps", "value": 0.05, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 417, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 419, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": 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{"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 437, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 439, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 444, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 446, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.010107, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 448, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "generic_message", "value": "Starting performance mode", "time_ms": 0.015701, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 841, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.021829, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 1.960540, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "generated_samples_per_query", "value": 1, "time_ms": 1.960540, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 1.960540, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 1.994116, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "issue_query_controller.cc", "line_no": 482, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 2894.689790, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 2894.689790, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 2894.689790, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 2894.689790, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 2894.689790, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 2894.689790, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "power_begin", "value": "09-26-2024 04:52:48.847", "time_ms": 2894.690743, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "power_end", "value": "09-26-2024 04:52:51.739", "time_ms": 2894.690743, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 655, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 660, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 661, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 662, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "early_stopping_result", "value": "", "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 682, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_query_count", "value": 1, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 692, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_samples_per_second", "value": 0.345721, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 748, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_min_latency_ns", "value": 2892504940, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 754, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_max_latency_ns", "value": 2892504940, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 755, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 2892504940, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 756, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 2892504940, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 2892504940, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 2892504940, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 2892504940, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 2892504940, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2851, "tid": 2851}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 2892504940, "time_ms": 2894.711302, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 2851, "tid": 2851}} diff --git a/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..b87b81a --- /dev/null +++ b/open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,51 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 0.345721 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 2892504940 +Max latency (ns) : 2892504940 +Mean latency (ns) : 2892504940 +50.00 percentile latency (ns) : 2892504940 +90.00 percentile latency (ns) : 2892504940 +95.00 percentile latency (ns) : 2892504940 +97.00 percentile latency (ns) : 2892504940 +99.00 percentile latency (ns) : 2892504940 +99.90 percentile latency (ns) : 2892504940 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 1 +target_qps : 0.05 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 1 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 5000 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/MLCommons/systems/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base.json b/open/MLCommons/systems/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base.json new file mode 100644 index 0000000..32f1556 --- /dev/null +++ b/open/MLCommons/systems/3b07702db56d-reference-gpu-pytorch_v2.4.1-scc24-base.json @@ -0,0 +1,37 @@ +{ + "accelerator_frequency": "2520000 MHz", + "accelerator_host_interconnect": "N/A", + "accelerator_interconnect": "N/A", + "accelerator_interconnect_topology": "", + "accelerator_memory_capacity": "23.64703369140625 GB", + "accelerator_memory_configuration": "N/A", + "accelerator_model_name": "NVIDIA GeForce RTX 4090", + "accelerator_on-chip_memories": "", + "accelerators_per_node": 1, + "cooling": "air", + "division": "open", + "framework": "pytorch v2.4.1", + "host_memory_capacity": "192G", + "host_memory_configuration": "undefined", + "host_network_card_count": "1", + "host_networking": "Gig Ethernet", + "host_networking_topology": "N/A", + 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", + "system_name": "gh_action", + "system_type": "edge", + "system_type_detail": "edge server" +} \ No newline at end of file diff --git a/open/UNM-Roadrunners/code/stable-diffusion-xl/README.md b/open/UNM-Roadrunners/code/stable-diffusion-xl/README.md new file mode 100644 index 0000000..2fd9f95 --- /dev/null +++ b/open/UNM-Roadrunners/code/stable-diffusion-xl/README.md @@ -0,0 +1 @@ +TBD \ No newline at end of file diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/README.md b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/README.md new file mode 100644 index 0000000..5629cd1 --- /dev/null +++ b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|-----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (15.17022, 235.68988) | 0.667 | - | \ No newline at end of file diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base.json b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base.json new file mode 100644 index 0000000..d47b6cc --- /dev/null +++ b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base.json @@ -0,0 +1,7 @@ +{ + "starting_weights_filename": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0", + "retraining": "no", + "input_data_types": "fp32", + "weight_data_types": "fp32", + "weight_transformations": "no" +} \ No newline at end of file diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/README.md b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..ff7a067 --- /dev/null +++ b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/README.md @@ -0,0 +1,56 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-5.14.0-427.37.1.el9_4.x86_64-x86_64-with-glibc2.35 +* CPU version: x86_64 +* Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] +* MLCommons CM version: 3.0.1 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo mlcommons@cm4mlops --checkout=769bf6afb15058ab9699c8b708fc484cc9c7b7fb + +cm run script \ + --tags=run-mlperf,inference,_r4.1-dev,_short,_scc24-base \ + --model=sdxl \ + --implementation=reference \ + --framework=pytorch \ + --category=datacenter \ + --scenario=Offline \ + --execution_mode=test \ + --device=cuda \ + --quiet \ + --precision=float16 +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload mlcommons@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo mlcommons@cm4mlops +cm pull repo mlcommons@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: 4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base + +Model Precision: fp32 + +### Accuracy Results +`CLIP_SCORE`: `15.17022`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `235.68988`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `0.666646` diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy_console.out b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy_console.out new file mode 100644 index 0000000..e69de29 diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/cm-version-info.json b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/cm-version-info.json new file mode 100644 index 0000000..6cc3978 --- /dev/null +++ b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/cm-version-info.json @@ -0,0 +1,464 @@ +{ + 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Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/os_info.json 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"0.44.0", + "zipp": "3.20.2" + } +} \ No newline at end of file diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/user.conf b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/user.conf new file mode 100644 index 0000000..21df3f1 --- /dev/null +++ b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/user.conf @@ -0,0 +1,5 @@ +stable-diffusion-xl.Offline.target_qps = 0.05 +stable-diffusion-xl.Offline.max_query_count = 10 +stable-diffusion-xl.Offline.min_query_count = 10 +stable-diffusion-xl.Offline.min_duration = 0 +stable-diffusion-xl.Offline.sample_concatenate_permutation = 0 diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/README.md b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/README.md new file mode 100644 index 0000000..a70c792 --- /dev/null +++ b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (13.90686, 84.21082) | 0.666 | - | \ No newline at end of file diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main.json b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main.json new file mode 100644 index 0000000..d47b6cc --- /dev/null +++ b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main.json @@ -0,0 +1,7 @@ +{ + "starting_weights_filename": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0", + "retraining": "no", + "input_data_types": "fp32", + "weight_data_types": "fp32", + "weight_transformations": "no" +} \ No newline at end of file diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/README.md b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..4d11a20 --- /dev/null +++ b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/README.md @@ -0,0 +1,56 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-5.14.0-427.37.1.el9_4.x86_64-x86_64-with-glibc2.35 +* CPU version: x86_64 +* Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] +* MLCommons CM version: 3.0.1 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo mlcommons@cm4mlops --checkout=769bf6afb15058ab9699c8b708fc484cc9c7b7fb + +cm run script \ + --tags=run-mlperf,inference,_r4.1-dev,_short,_scc24-main \ + --model=sdxl \ + --implementation=reference \ + --framework=pytorch \ + --category=datacenter \ + --scenario=Offline \ + --execution_mode=test \ + --device=cuda \ + --quiet \ + --precision=float16 +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload mlcommons@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo mlcommons@cm4mlops +cm pull repo mlcommons@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: 4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main + +Model Precision: fp32 + +### Accuracy Results +`CLIP_SCORE`: `13.90686`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `84.21082`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `0.665545` diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy_console.out b/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy_console.out new file mode 100644 index 0000000..e69de29 diff --git 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Value is mostly int64_t. +# Model maybe '*' as wildcard. In that case the value applies to all models. +# All times are in milli seconds + +# Set performance_sample_count for each model. +# User can optionally set this to higher values in user.conf. +resnet50.*.performance_sample_count_override = 1024 +ssd-mobilenet.*.performance_sample_count_override = 256 +retinanet.*.performance_sample_count_override = 64 +bert.*.performance_sample_count_override = 10833 +dlrm.*.performance_sample_count_override = 204800 +dlrm-v2.*.performance_sample_count_override = 204800 +rnnt.*.performance_sample_count_override = 2513 +gptj.*.performance_sample_count_override = 13368 +llama2-70b.*.performance_sample_count_override = 24576 +stable-diffusion-xl.*.performance_sample_count_override = 5000 +# set to 0 to let entire sample set to be performance sample +3d-unet.*.performance_sample_count_override = 0 + +# Set seeds. The seeds will be distributed two weeks before the submission. +*.*.qsl_rng_seed = 3066443479025735752 +*.*.sample_index_rng_seed = 10688027786191513374 +*.*.schedule_rng_seed = 14962580496156340209 +# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission. +*.*.test05_qsl_rng_seed = 16799458546791641818 +*.*.test05_sample_index_rng_seed = 5453809927556429288 +*.*.test05_schedule_rng_seed = 5435552105434836064 + + +*.SingleStream.target_latency_percentile = 90 +*.SingleStream.min_duration = 600000 + +*.MultiStream.target_latency_percentile = 99 +*.MultiStream.samples_per_query = 8 +*.MultiStream.min_duration = 600000 +*.MultiStream.min_query_count = 662 +retinanet.MultiStream.target_latency = 528 + +# 3D-UNet uses equal issue mode because it has non-uniform inputs +3d-unet.*.sample_concatenate_permutation = 1 + +# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario +gptj.*.sample_concatenate_permutation = 1 +llama2-70b.*.sample_concatenate_permutation = 1 +mixtral-8x7b.*.sample_concatenate_permutation = 1 + +*.Server.target_latency = 10 +*.Server.target_latency_percentile = 99 +*.Server.target_duration = 0 +*.Server.min_duration = 600000 +resnet50.Server.target_latency = 15 +retinanet.Server.target_latency = 100 +bert.Server.target_latency = 130 +dlrm.Server.target_latency = 60 +dlrm-v2.Server.target_latency = 60 +rnnt.Server.target_latency = 1000 +gptj.Server.target_latency = 20000 +stable-diffusion-xl.Server.target_latency = 20000 +# Llama2-70b benchmarks measures token latencies +llama2-70b.*.use_token_latencies = 1 +mixtral-8x7b.*.use_token_latencies = 1 +# gptj benchmark infers token latencies +gptj.*.infer_token_latencies = 1 +gptj.*.token_latency_scaling_factor = 69 +# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0 +llama2-70b.Server.target_latency = 0 +llama2-70b.Server.ttft_latency = 2000 +llama2-70b.Server.tpot_latency = 200 + +mixtral-8x7b.Server.target_latency = 0 +mixtral-8x7b.Server.ttft_latency = 2000 +mixtral-8x7b.Server.tpot_latency = 200 + +*.Offline.target_latency_percentile = 90 +*.Offline.min_duration = 600000 + +# In Offline scenario, we always have one query. But LoadGen maps this to +# min_sample_count internally in Offline scenario. If the dataset size is larger +# than 24576 we limit the min_query_count to 24576 and otherwise we use +# the dataset size as the limit + +resnet50.Offline.min_query_count = 24576 +retinanet.Offline.min_query_count = 24576 +dlrm-v2.Offline.min_query_count = 24576 +bert.Offline.min_query_count = 10833 +gptj.Offline.min_query_count = 13368 +rnnt.Offline.min_query_count = 2513 +3d-unet.Offline.min_query_count = 43 +stable-diffusion-xl.Offline.min_query_count = 5000 +llama2-70b.Offline.min_query_count = 24576 +mixtral-8x7b.Offline.min_query_count = 15000 + +# These fields should be defined and overridden by user.conf. +*.SingleStream.target_latency = 10 +*.MultiStream.target_latency = 80 +*.Server.target_qps = 1.0 +*.Offline.target_qps = 1.0 diff --git a/open/UNM-Roadrunners/measurements/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/os_info.json 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{"key": "qsl_name", "value": "PyQSL", "time_ms": 0.019028, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1201, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "qsl_reported_total_count", "value": 50, "time_ms": 0.019028, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1202, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.019028, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1203, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 270, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_test_mode", "value": "AccuracyOnly", "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 271, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 308, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 314, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 315, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_min_query_count", "value": 50, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_max_query_count", "value": 50, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 318, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 319, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 321, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_accuracy_log_rng_seed", "value": 0, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 322, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_accuracy_log_probability", "value": 0, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 324, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_accuracy_log_sampling_target", "value": 0, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 326, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_print_timestamps", "value": false, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 328, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_performance_issue_unique", "value": false, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 329, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_performance_sample_count_override", "value": 5000, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "requested_sample_concatenate_permutation", "value": false, "time_ms": 0.023953, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 337, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_scenario", "value": "Offline", "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 413, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_test_mode", "value": "AccuracyOnly", "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 414, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_samples_per_query", "value": 50, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 416, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_target_qps", "value": 0.05, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 417, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 419, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_max_async_queries", "value": 1, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 421, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_target_duration_ms", "value": 0, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 422, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_min_duration_ms", "value": 0, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 424, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_max_duration_ms", "value": 0, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 425, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_max_query_count", "value": 50, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 427, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_min_sample_count", "value": 50, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 428, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 430, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 432, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 437, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 439, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 444, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 446, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.024065, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 448, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "generic_message", "value": "Starting accuracy mode", "time_ms": 0.030482, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1090, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "loaded_qsl_set", "value": [25,24,46,36,21,22,39,13,45,4,32,40,33,23,10,44,34,15,28,29,3,30,1,47,26,31,16,8,2,0,49,27,48,5,17,19,20,18,43,9,14,6,35,7,12,37,11,38,42,41], "time_ms": 0.040568, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 613, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 3.092280, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "generated_samples_per_query", "value": 50, "time_ms": 3.092280, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 429, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 3.092280, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 430, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 75552.876347, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 898, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 75552.876347, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 900, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 75552.876347, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 75552.876347, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 75552.876347, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 75552.876347, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "power_begin", "value": "10-07-2024 16:43:27.745", "time_ms": 75552.880387, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 564, "pid": 5677, "tid": 5677}} +:::MLLOG {"key": "power_end", "value": "10-07-2024 16:44:43.276", "time_ms": 75552.880387, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 5677, "tid": 5677}} diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..b79fa7e --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt @@ -0,0 +1,87 @@ +:::MLLOG {"key": "loadgen_version", "value": "4.1 @ 41fa8aadd1", "time_ms": 0.005221, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 4114, "tid": 4114}} +:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-10-07T16:36:33.041324", "time_ms": 0.005221, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 4114, "tid": 4114}} +:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-10-07T16:36:33.041331", "time_ms": 0.005221, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 4114, "tid": 4114}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-10-01T18:00:17+01:00", "time_ms": 0.005221, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 4114, "tid": 4114}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "41fa8aadd1ba0ecc97f6a519d8b42b04278e5f24 Add format files github action (#1682)\n518b454fd8647bfbd23a074e875e87353f33393e Tflite tpu (#1449)\ne0fdec1c7a75c98cfc194f13d62ac4388d419c8a Fix link in GettingStarted.ipynb (#1512)\n92bd8198d15411d7fb7d7c27f8904bc5a0bcfe7a Fix warning in the submission checker (#1808)\n224cfbf5c0e82cae6d48620025b7e1258ae3666a Fix typo in reference datatype (#1851)", "time_ms": 0.005221, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 4114, "tid": 4114}} +:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.005221, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 4114, "tid": 4114}} +:::MLLOG 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+:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 15000468530, "time_ms": 15005.234826, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 4114, "tid": 4114}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 15000468530, "time_ms": 15005.234826, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 4114, "tid": 4114}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 15000468530, "time_ms": 15005.234826, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 4114, "tid": 4114}} diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..dd18cce --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,51 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 0.666646 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 1640448723 +Max latency (ns) : 15000468530 +Mean latency (ns) : 8311693474 +50.00 percentile latency (ns) : 9048469000 +90.00 percentile latency (ns) : 15000468530 +95.00 percentile latency (ns) : 15000468530 +97.00 percentile latency (ns) : 15000468530 +99.00 percentile latency (ns) : 15000468530 +99.90 percentile latency (ns) : 15000468530 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 10 +target_qps : 0.05 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 10 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 5000 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/accuracy.txt b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/accuracy.txt new file mode 100644 index 0000000..f2f2fe1 --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/accuracy.txt @@ -0,0 +1,2 @@ +Accuracy Results: {'FID_SCORE': 84.21082273715388, 'CLIP_SCORE': 13.906862080842256} +hash=44fa2d532b0bbd7a6787a7ee90d79e2b973adb835514b69bfca8d4fab790ef69 diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/images/109.png 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b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/images/captions.txt new file mode 100644 index 0000000..102b05d --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/images/captions.txt @@ -0,0 +1,10 @@ +4655 Close up of a red fire hydrant near a sidewalk. +2569 A dark table has a large arrangement of food. +1303 A baby boy standing inside of a wooden crib. +109 People walking toward an airplane to board it. +4509 a couple of horses grazing on some green grass +3009 A horse that is standing with a cart near birds. +2179 A man holds up a Polish sausage on a bun. +1826 Two dogs resting comfortably on a tiled floor. +2094 A cat hiding in a basket of some sort. +3340 Vintage picture of a man and a horse on the farm. diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json new file mode 100644 index 0000000..f58e8b5 --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json @@ -0,0 +1,7 @@ +[ +{ "seq_id" : 0, "qsl_idx" : 230, "data" : 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+:::MLLOG {"key": "power_end", "value": "10-07-2024 17:00:12.606", "time_ms": 750444.743838, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 566, "pid": 16406, "tid": 16406}} diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt new file mode 100644 index 0000000..a05d865 --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt @@ -0,0 +1,4 @@ + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json new file mode 100644 index 0000000..0d4f101 --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json @@ -0,0 +1,2 @@ +[ +] diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt new file mode 100644 index 0000000..c6a2b0e --- /dev/null +++ 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"tid": 14843}} +:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-10-01T18:00:17+01:00", "time_ms": 0.006739, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 14843, "tid": 14843}} +:::MLLOG {"key": "loadgen_git_log_message", "value": "41fa8aadd1ba0ecc97f6a519d8b42b04278e5f24 Add format files github action (#1682)\n518b454fd8647bfbd23a074e875e87353f33393e Tflite tpu (#1449)\ne0fdec1c7a75c98cfc194f13d62ac4388d419c8a Fix link in GettingStarted.ipynb (#1512)\n92bd8198d15411d7fb7d7c27f8904bc5a0bcfe7a Fix warning in the submission checker (#1808)\n224cfbf5c0e82cae6d48620025b7e1258ae3666a Fix typo in reference datatype (#1851)", "time_ms": 0.006739, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 14843, "tid": 14843}} +:::MLLOG {"key": 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"tid": 14843}} +:::MLLOG {"key": "result_mean_latency_ns", "value": 8316218601, "time_ms": 15056.002409, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 756, "pid": 14843, "tid": 14843}} +:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 9051526247, "time_ms": 15056.002409, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 14843, "tid": 14843}} +:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 15025285544, "time_ms": 15056.002409, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 14843, "tid": 14843}} +:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 15025285544, "time_ms": 15056.002409, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 14843, "tid": 14843}} +:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 15025285544, "time_ms": 15056.002409, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 14843, "tid": 14843}} +:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 15025285544, "time_ms": 15056.002409, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 14843, "tid": 14843}} +:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 15025285544, "time_ms": 15056.002409, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 758, "pid": 14843, "tid": 14843}} diff --git a/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt new file mode 100644 index 0000000..325a8f2 --- /dev/null +++ b/open/UNM-Roadrunners/results/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt @@ -0,0 +1,51 @@ +================================================ +MLPerf Results Summary +================================================ +SUT name : PySUT +Scenario : Offline +Mode : PerformanceOnly +Samples per second: 0.665545 +Result is : VALID + Min duration satisfied : Yes + Min queries satisfied : Yes + Early stopping satisfied: Yes + +================================================ +Additional Stats +================================================ +Min latency (ns) : 1628914908 +Max latency (ns) : 15025285544 +Mean latency (ns) : 8316218601 +50.00 percentile latency (ns) : 9051526247 +90.00 percentile latency (ns) : 15025285544 +95.00 percentile latency (ns) : 15025285544 +97.00 percentile latency (ns) : 15025285544 +99.00 percentile latency (ns) : 15025285544 +99.90 percentile latency (ns) : 15025285544 + +================================================ +Test Parameters Used +================================================ +samples_per_query : 10 +target_qps : 0.05 +target_latency (ns): 0 +max_async_queries : 1 +min_duration (ms): 0 +max_duration (ms): 0 +min_query_count : 1 +max_query_count : 10 +qsl_rng_seed : 3066443479025735752 +sample_index_rng_seed : 10688027786191513374 +schedule_rng_seed : 14962580496156340209 +accuracy_log_rng_seed : 0 +accuracy_log_probability : 0 +accuracy_log_sampling_target : 0 +print_timestamps : 0 +performance_issue_unique : 0 +performance_issue_same : 0 +performance_issue_same_index : 0 +performance_sample_count : 5000 + +No warnings encountered during test. + +No errors encountered during test. diff --git a/open/UNM-Roadrunners/systems/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base.json b/open/UNM-Roadrunners/systems/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base.json new file mode 100644 index 0000000..6cd1d9a --- /dev/null +++ b/open/UNM-Roadrunners/systems/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-base.json @@ -0,0 +1,37 @@ +{ + "accelerator_frequency": "1785000 MHz", + "accelerator_host_interconnect": "N/A", + "accelerator_interconnect": "N/A", + "accelerator_interconnect_topology": "", + "accelerator_memory_capacity": "93.11541748046875 GB", + "accelerator_memory_configuration": "N/A", + "accelerator_model_name": "NVIDIA H100 NVL", + "accelerator_on-chip_memories": "", + "accelerators_per_node": 3, + "cooling": "air", + "division": "open", + "framework": "pytorch v2.4.1", + "host_memory_capacity": "2.1T", + "host_memory_configuration": "undefined", + "host_network_card_count": "1", + "host_networking": "Gig Ethernet", + "host_networking_topology": "N/A", + "host_processor_caches": "L1d cache: 5.6 MiB (120 instances), L1i cache: 3.8 MiB (120 instances), L2 cache: 240 MiB (120 instances), L3 cache: 600 MiB (2 instances)", + "host_processor_core_count": "60", + "host_processor_frequency": "undefined", + "host_processor_interconnect": "", + "host_processor_model_name": "INTEL(R) XEON(R) PLATINUM 8580", + "host_processors_per_node": "2", + "host_storage_capacity": "17T", + "host_storage_type": "SSD", + "hw_notes": "", + "number_of_nodes": "1", + "operating_system": "Ubuntu 22.04 (linux-5.14.0-427.37.1.el9_4.x86_64-glibc2.35)", + "other_software_stack": "Python: 3.10.12, LLVM-15.0.6", + "status": "available", + "submitter": "UNM-Roadrunners", + "sw_notes": "Automated by MLCommons CM v3.0.1. ", + "system_name": "4751fbf98487", + "system_type": "datacenter", + "system_type_detail": "edge server" +} \ No newline at end of file diff --git a/open/UNM-Roadrunners/systems/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main.json b/open/UNM-Roadrunners/systems/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main.json new file mode 100644 index 0000000..6cd1d9a --- /dev/null +++ b/open/UNM-Roadrunners/systems/4751fbf98487-reference-gpu-pytorch_v2.4.1-scc24-main.json @@ -0,0 +1,37 @@ +{ + "accelerator_frequency": "1785000 MHz", + "accelerator_host_interconnect": "N/A", + "accelerator_interconnect": "N/A", + "accelerator_interconnect_topology": "", + "accelerator_memory_capacity": "93.11541748046875 GB", + "accelerator_memory_configuration": "N/A", + "accelerator_model_name": "NVIDIA H100 NVL", + "accelerator_on-chip_memories": "", + "accelerators_per_node": 3, + "cooling": "air", + "division": "open", + "framework": "pytorch v2.4.1", + "host_memory_capacity": "2.1T", + "host_memory_configuration": "undefined", + "host_network_card_count": "1", + "host_networking": "Gig Ethernet", + "host_networking_topology": "N/A", + "host_processor_caches": "L1d cache: 5.6 MiB (120 instances), L1i cache: 3.8 MiB (120 instances), L2 cache: 240 MiB (120 instances), L3 cache: 600 MiB (2 instances)", + "host_processor_core_count": "60", + "host_processor_frequency": "undefined", + "host_processor_interconnect": "", + "host_processor_model_name": "INTEL(R) XEON(R) PLATINUM 8580", + "host_processors_per_node": "2", + "host_storage_capacity": "17T", + "host_storage_type": "SSD", + "hw_notes": "", + "number_of_nodes": "1", + "operating_system": "Ubuntu 22.04 (linux-5.14.0-427.37.1.el9_4.x86_64-glibc2.35)", + "other_software_stack": "Python: 3.10.12, LLVM-15.0.6", + "status": "available", + "submitter": "UNM-Roadrunners", + "sw_notes": "Automated by MLCommons CM v3.0.1. ", + "system_name": "4751fbf98487", + "system_type": "datacenter", + "system_type_detail": "edge server" +} \ No newline at end of file diff --git a/process.py b/process.py new file mode 100644 index 0000000..c0694bf --- /dev/null +++ b/process.py @@ -0,0 +1,337 @@ +import json +import os + +def getuniquevalues(data, key): + uniquevalues = [] + for item in data: + if item.get(key) and item.get(key) not in uniquevalues: + uniquevalues.append(item[key]) + return uniquevalues + +with open('summary_results.json') as f: + data = json.load(f) +models_all = getuniquevalues(data, "Model") +models_all.insert(0, "All models") +platforms = getuniquevalues(data, "Platform") +#print(models_all) +#print(platforms) + + +def filterdata(data, keys, values): + filtered_data = [] + for item in data: + mismatch = False + for key,value in zip(keys, values): + if item.get(key) != value: + mismatch = True + break + if not mismatch: + filtered_data.append(item) + return filtered_data + +def construct_table(scenario, models, data1, data2, is_power, results1, results2): + # Initialize the HTML table with the header + html = f'
' + html += "" + + # Table header + tableheader = f""" + + + + """ + + if is_power: + tableheader += """ + + + + + + """ + + tableheader += "" + + # Add header and footer + html += tableheader + html += "" + #html += f"{tableheader}" + + # Initialize performance title (not used in the original PHP code, but included for completeness) + performance_title = "Samples per Second" + + # Generate table rows + for row in models: + html += "" + html += f"" + + perf1 = round(results1[row]['Performance_Result'], 1) + perf2 = round(results2[row]['Performance_Result'], 1) + + if perf2: + perfdelta = round((1 - (perf1 / perf2)),4) * 100 + perfdelta = round(perfdelta, 1) + else: + perfdelta = "" + + html += f"" + html += f"" + html += f"" + + if is_power: + pow1 = results1[row]['Power_Result'] + pow2 = results2[row]['Power_Result'] + + if pow2: + powdelta = round(((1 - pow1 / pow2)), 4) * 100 + else: + powdelta = "" + + if pow1: + peff1 = round(perf1 / pow1, 5) + else: + peff1 = "" + + if pow2: + peff2 = round(perf2 / pow2, 5) + else: + peff2 = "" + + html += f"" + html += f"" + html += f"" + html += f"" + html += f"
Model{data1}{data2}Performance DeltaPower 1Power 2Power DeltaPower Efficiency 1Power Efficiency 2Power Efficiency Delta
{row}{perf1}{perf2}{perfdelta}%{pow1}{pow2}{powdelta}%{peff1} + var data1 = {}, data2 = {}, draw_power = {}, draw_power_efficiency = {}, ytitle = {}, sortcolumnindex, perfsortorder; + + """ + + customid = 1 + for scenario in scenarios: + keys = [ "Scenario", "Platform", "version" ] + values = [ scenario, system1, sysversion1 ] + result1 = filterdata(data, keys, values) + content[f'custom_{customid}'] = f"" + + values = [ scenario, system2, sysversion2 ] + result2 = filterdata(data, keys, values) + result2 = filterdata(data, keys, values) + if len(result1) == 0 or len(result2) == 0: + display_string=f"""style="display:none" + """ + else: + display_string ="" + + + is_power = len(result2) > 0 and (result2[0]['has_power']) + power_string = "true" if is_power else "false" + + data1_str = f"{sysversion1}: {system1}" + data2_str = f"{sysversion2}: {system2}" + ytitle = ytitle_scenarios[scenario] + + content[f'custom_{customid}'] = f""" + + """ + + models = [] + result2_models = [row['Model'] for row in result2] + for row in result1: + if row['Model'] not in models and row['Model'] in result2_models: + models.append(row['Model']) + + results1 = {model: row for model in models for row in result1 if row['Model'] == model} + results2 = {model: row for model in models for row in result2 if row['Model'] == model} + + tableposthtml = """ + +
+ + + + + + + +
+ """ + + html = f"""

Comparing {scenario} scenario for {data1_str} and {data2_str}

""" + tableposthtml + htmltable = construct_table(scenario, models, data1_str, data2_str, is_power, results1, results2) + html += htmltable + html += tableposthtml + + content[f'custom_{customid}'] += html + + resultjson = json.dumps(result1) # or any appropriate variable + + content[f'custom_{customid}'] += f""" +
+ + """ + content[f'custom_{customid}'] += f""" +
+ +
+ + """ + + content[f'custom_{customid}'] += f""" +
+
+ """ + + customid += 1 + + return content + + +#print(data) +def generate_html_form(platforms, models_all, data1=None, data2=None, modelsdata=None): + # Setting default values if not provided + if not data1: + data1 = '' + if not data2: + data2 = '' + if not modelsdata: + modelsdata = 'All models' + + # Create select options for system 1 and system 2 + def generate_select_options(options, selected_value): + html = "" + #print(options) + for key, value in options.items(): + selected = 'selected' if value == selected_value else '' + html += f"\n" + return html + + system1_options = generate_select_options(platforms, data1) + system2_options = generate_select_options(platforms, data2) + + # Create select options for models + models_options = generate_select_options(models_all, modelsdata) + + # Generate the HTML for the form + html_form = f""" +
+

Compare Results

+ +
+ + +
+ +
+ + +
+ +
+ + +
+ +
+ +
+
+ """ + + return html_form + +system1 = "1xMI300X_2EPYC-937F" +system2 = "8xMI300X_2EPYC-937F" +sysversion1 = "v4.1" +sysversion2 = "v4.1" +modelfilterstring = "" + +content = process_scenarios(system1, system2, sysversion1, sysversion2, modelfilterstring) + +out_html = "" + +for key,value in content.items(): + out_html += "\n" + value +out_html += """ + + +""" + +out_html += """ + +""" + +#print(content) +data1 = None +data2 = None +modelsdata = None +platforms_data = {v:k for v,k in enumerate(platforms)} +models_data = {v:k for v,k in enumerate(models_all)} +# Generate the HTML form +html_form = generate_html_form(platforms_data, models_data, data1, data2, modelsdata) + +# Output the generated HTML +out_html = f"""--- +hide: + - toc +--- + + +{out_html}{html_form} + +""" + +out_path = os.path.join("docs", "compare", "index.md") + +if not os.path.exists(os.path.dirname(out_path)): + os.makedirs(os.path.dirname(out_path)) + +with open(out_path, "w") as f: + f.write(out_html) + +#print(out_html) + + diff --git a/process_results_table.py b/process_results_table.py new file mode 100644 index 0000000..9d332e4 --- /dev/null +++ b/process_results_table.py @@ -0,0 +1,466 @@ +import json +import os +import time + +with open('summary_results.json') as f: + data = json.load(f) +#print(models_all) +#print(platforms) + +tableposhtml = """ + +
+ + + + + + + +
+ """ + +def get_json_files(github_url): + import requests + from bs4 import BeautifulSoup + + retries = 5 + retry_delay = 2 + + for attempt in range(retries): + try: + # Get the content of the GitHub page + response = requests.get(github_url) + soup = BeautifulSoup(response.text, 'html.parser') + + # Find all JSON files + #print(soup) + # Find the + + + + +""" + +out_html = f"""--- +hide: + - navigation + - toc +--- + + +{html} +{extra_scripts} + +""" +with open(os.path.join("docs", "index.md"), "w") as f: + f.write(out_html) + + +#print(data) + + diff --git a/run.sh b/run.sh new file mode 100644 index 0000000..3811bce --- /dev/null +++ b/run.sh @@ -0,0 +1 @@ +INFERENCE_RESULTS_VERSION=v4.1 INFERENCE_RESULTS_REPO_OWNER=GATEOverflow INFERENCE_RESULTS_REPO_BRANCH=mlperf-inference-results-scc24 INFERENCE_RESULTS_REPO_NAME=cm4mlperf-inference bash docinit.sh diff --git a/summary.csv b/summary.csv new file mode 100644 index 0000000..6b1558b --- /dev/null +++ b/summary.csv @@ -0,0 +1,9 @@ +Organization,Availability,Division,SystemType,SystemName,Platform,Model,MlperfModel,Scenario,Result,Accuracy,number_of_nodes,host_processor_model_name,host_processors_per_node,host_processor_core_count,accelerator_model_name,accelerators_per_node,Location,framework,operating_system,notes,compliance,errors,version,inferred,has_power,Units,weight_data_types +MLCommons,available,open,"datacenter","48ed6105bd85",48ed6105bd85-nvidia-gpu-TensorRT-scc24-main,stable-diffusion-xl,stable-diffusion-xl,Offline,1.13292,CLIP_SCORE: 15.586050063371658 FID_SCORE: 236.8087101317688,1,"Intel(R) Xeon(R) w7-2495X",1,24,"NVIDIA GeForce RTX 4090","1",open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-main/stable-diffusion-xl/offline,"TensorRT","Ubuntu 20.04 (linux-6.2.0-39-generic-glibc2.31)","Automated by MLCommons CM v2.3.6. ",1,0,v4.1,0,False,Samples/s,"int8" +MLCommons,available,open,"datacenter","e8dbfdd7ca14",e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base,stable-diffusion-xl,stable-diffusion-xl,Offline,1.13521,CLIP_SCORE: 15.617164582014084 FID_SCORE: 233.28573789198563,1,"Intel(R) Xeon(R) w7-2495X",1,24,"NVIDIA GeForce RTX 4090","1",open/MLCommons/results/e8dbfdd7ca14-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline,"TensorRT","Ubuntu 20.04 (linux-6.2.0-39-generic-glibc2.31)","Automated by MLCommons CM v2.3.9. ",1,0,v4.1,0,False,Samples/s,"int8" +MLCommons,available,open,"datacenter","48ed6105bd85",48ed6105bd85-nvidia-gpu-TensorRT-scc24-base,stable-diffusion-xl,stable-diffusion-xl,Offline,1.13598,CLIP_SCORE: 15.586050063371658 FID_SCORE: 236.8087101317688,1,"Intel(R) Xeon(R) w7-2495X",1,24,"NVIDIA GeForce RTX 4090","1",open/MLCommons/results/48ed6105bd85-nvidia-gpu-TensorRT-scc24-base/stable-diffusion-xl/offline,"TensorRT","Ubuntu 20.04 (linux-6.2.0-39-generic-glibc2.31)","Automated by MLCommons CM v2.3.6. ",1,0,v4.1,0,False,Samples/s,"int8" +MLCommons,available,open,"edge","gh_action",gh_action-reference-gpu-pytorch_v2.4.1-default_config,gptj-99,gptj-99,Offline,52.9478,,1,"Intel(R) Xeon(R) w7-2495X",1,24,"NVIDIA GeForce RTX 4090","1",open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/gptj-99/offline,"pytorch v2.4.1","Ubuntu 22.04 (linux-6.2.0-39-generic-glibc2.35)","Automated by MLCommons CM v2.3.4. ",1,0,v4.1,0,False,Tokens/s,"fp32" +MLCommons,available,open,"edge","gh_action",gh_action-reference-gpu-pytorch_v2.4.1-default_config,stable-diffusion-xl,stable-diffusion-xl,Offline,0.345721,CLIP_SCORE: 15.18544016778469 FID_SCORE: 235.69504308101006,1,"Intel(R) Xeon(R) w7-2495X",1,24,"NVIDIA GeForce RTX 4090","1",open/MLCommons/results/gh_action-reference-gpu-pytorch_v2.4.1-default_config/stable-diffusion-xl/offline,"pytorch v2.4.1","Ubuntu 22.04 (linux-6.2.0-39-generic-glibc2.35)","Automated by MLCommons CM v2.3.4. ",1,0,v4.1,0,False,Samples/s,"fp32" +MLCommons,available,open,"datacenter","48ed6105bd85",48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base,stable-diffusion-xl,stable-diffusion-xl,Offline,0.373636,CLIP_SCORE: 15.236237794160843 FID_SCORE: 238.78369342212613,1,"Intel(R) Xeon(R) w7-2495X",1,24,"NVIDIA GeForce RTX 4090","1",open/MLCommons/results/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline,"TensorRT","Ubuntu 20.04 (linux-6.2.0-39-generic-glibc2.31)","Automated by MLCommons CM v2.3.6. ",1,0,v4.1,0,False,Samples/s,"fp32" +MLCommons,available,open,"datacenter","f9ac88850adc",f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base,stable-diffusion-xl,stable-diffusion-xl,Offline,0.376944,CLIP_SCORE: 15.18544016778469 FID_SCORE: 235.69504308101006,1,"Intel(R) Xeon(R) w7-2495X",1,24,"NVIDIA GeForce RTX 4090","1",open/MLCommons/results/f9ac88850adc-reference-gpu-pytorch_v2.4.1-scc24-base/stable-diffusion-xl/offline,"pytorch v2.4.1","Ubuntu 22.04 (linux-6.2.0-39-generic-glibc2.35)","Automated by MLCommons CM v2.3.9. 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