diff --git a/.github/lib-filters.yaml b/.github/lib-filters.yaml new file mode 100644 index 00000000..ba829cba --- /dev/null +++ b/.github/lib-filters.yaml @@ -0,0 +1,25 @@ +# define filters for file changes +# to trigger unit tests + +# filter for changes +# to workflow +workflow: &workflow + - '.github/lib-filters.yaml' + - '.github/workflows/lib-tests.yaml' + + +# use paths for filter names +# for simplicity in ci-test.yaml + +# cleaner way to run all jobs +# if workflow file is changed? + +# libraries +architectures: + - *workflow + - 'libs/architectures/**' + - 'ml4gw/**' + +ledger: + - *workflow + - 'libs/ledger/**' diff --git a/.github/project-filters.yaml b/.github/project-filters.yaml new file mode 100644 index 00000000..0dbe8a02 --- /dev/null +++ b/.github/project-filters.yaml @@ -0,0 +1,29 @@ +workflow: &workflow + - '.github/lib-filters.yaml' + - '.github/workflows/lib-tests.yaml' + +data: + - *workflow + - 'projects/data/**' + - 'ml4gw/**' + - 'libs/ledger/**' + - 'libs/priors/**' + +infer: + - *workflow + - 'projects/infer/**' + - 'hermes/**' + - 'libs/ledger/**' + +train: + - *workflow + - 'projects/train/**' + - 'ml4gw/**' + - 'libs/ledger/**' + - 'libs/architectures/**' + +export: + - *workflow + - 'projects/export/**' + - 'ml4gw/**' + - 'hermes/**' diff --git a/.github/workflows/lib-tests.yaml b/.github/workflows/lib-tests.yaml new file mode 100644 index 00000000..2dba0aa8 --- /dev/null +++ b/.github/workflows/lib-tests.yaml @@ -0,0 +1,74 @@ +name: library tests + +on: + pull_request: + types: + - opened + - reopened + - synchronize + - ready_for_review + push: + branches: + - main + +jobs: + # first job users filters to output which libraries + # and projects have updates that need testing + changes: + runs-on: ubuntu-latest + outputs: + libraries: ${{ steps.filter.outputs.changes }} + steps: + - uses: actions/checkout@v2 + - uses: dorny/paths-filter@v2 + id: filter + with: + filters: .github/lib-filters.yaml + if: github.event.pull_request.draft == false + + # second job takes those outputs and runs + # unit tests on these libs and projects + tests: + runs-on: ubuntu-latest + needs: changes + strategy: + fail-fast: false # is this desired behavior here? + matrix: + library: ${{ fromJSON(needs.changes.outputs.libraries) }} + exclude: + # don't run non-existent .github/workflow tests, + # and exclude projects, whose tests are run in + # a different CI script + - library: 'workflow' + permissions: + packages: read + container: + # container with python and git + image: cicirello/pyaction:4.8 + volumes: + - ${{ github.workspace }}:/github/workspace + steps: + - uses: actions/checkout@v2 + with: + submodules: recursive + + # build the libraries environment + - + name: build environment + env: + test_dir: /github/workspace/libs/${{ matrix.library }} + run: | + python -m pip install poetry + cd $test_dir + poetry install + shell: bash + + # run its unit tests inside that environment + - + name: run tests + env: + test_dir: /github/workspace/libs/${{ matrix.library }} + run: | + cd $test_dir + poetry run pytest + shell: bash diff --git a/.github/workflows/container-build.yaml b/.github/workflows/project-build-test.yaml similarity index 55% rename from .github/workflows/container-build.yaml rename to .github/workflows/project-build-test.yaml index 7e5b476b..1e242b8e 100644 --- a/.github/workflows/container-build.yaml +++ b/.github/workflows/project-build-test.yaml @@ -4,25 +4,54 @@ # to convert between the formats in order to handle # the large memory footprints of our containers without # toppling over the GitHub runner nodes this executes on. -name: container-build -on: +name: project tests + +on: + pull_request: + types: + - opened + - reopened + - synchronize + - ready_for_review push: + branches: + - main + env: REGISTRY: ghcr.io + PATH: /opt/env/bin/:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/cuda-11.8/bin:/opt/tritonserver/bin:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin + jobs: - build: + changes: runs-on: ubuntu-latest + outputs: + projects: ${{ steps.filter.outputs.changes }} + steps: + - name: Checkout repository + uses: actions/checkout@v2 + - name: Filter project changes + id: filter + uses: dorny/paths-filter@v2 + with: + filters: .github/project-filters.yaml + if: github.event.pull_request.draft == false + + build-test: + runs-on: ubuntu-latest + needs: changes permissions: contents: read packages: write strategy: fail-fast: false matrix: - project: [train, export, data] + project: ${{ fromJSON(needs.changes.outputs.projects) }} + exclude: + - project: 'workflow' # Fixed the exclusion key steps: - - name: Delete huge unnecessary tools folder + name: delete huge unnecessary tools folder run: rm -rf /opt/hostedtoolcache - name: Checkout repository @@ -30,7 +59,7 @@ jobs: with: submodules: recursive - - name: Log in to the Container registry + name: log in to the Container registry uses: docker/login-action@65b78e6e13532edd9afa3aa52ac7964289d1a9c1 with: registry: ${{ env.REGISTRY }} @@ -44,7 +73,7 @@ jobs: # in one fell swoop because of permissions discrepancies # inside and outside the container. - - name: Build singularity image + name: build singularity image run: | docker run \ --rm \ @@ -53,13 +82,25 @@ jobs: --privileged \ --entrypoint /bin/bash \ quay.io/singularity/singularity:v3.8.1 \ - -c 'singularity build --sandbox /tmp/app apptainer.def && tar -czf /opt/aframe/app.tar.gz -C /tmp/app .' + -c 'singularity build --sandbox /opt/aframe/sandbox apptainer.def' + + + - name: run tests in singularity sandbox and tar + run: | + docker run \ + --rm \ + -v ${{ github.workspace }}:/opt/aframe \ + --workdir /opt/aframe/projects/${{ matrix.project }} \ + --privileged \ + --entrypoint /bin/bash \ + quay.io/singularity/singularity:v3.8.1 \ + -c 'singularity exec --env PATH=${{ env.PATH }} /opt/aframe/sandbox pytest && tar -czf /opt/aframe/app.tar.gz -C /opt/aframe/sandbox .' # now copy the fs contents into an empty # container and push it to the registry, # using a lowercase version of the tag since # the github environment variables are case-sensitive - # TODO: add step to run tests inside docker + # TODO: currently combining path for nvidia variables # necessary to launch triton in export container @@ -67,10 +108,14 @@ jobs: # Should add conditionals in this workflow to set these dynamically - name: build docker image + # only run on pushes + if: ${{ github.event_name == 'push' }} env: tag: ${{ env.REGISTRY }}/${{ github.repository }}/${{ matrix.project }}:${{ github.ref_name }} - path: /usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/cuda-11.8/bin:/opt/tritonserver/bin:/usr/local/mpi/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/ucx/bin run: | export TAG_LC=${tag,,} - cat app.tar.gz | docker import --change "ENV PATH=${{ env.path }}" - $TAG_LC + cat app.tar.gz | docker import --change "ENV PATH=${{ env.PATH }}" - $TAG_LC docker push $TAG_LC + + + diff --git a/libs/architectures/architectures/networks/wavenet.py b/libs/architectures/architectures/networks/wavenet.py index 59ab00cc..0d0c0508 100644 --- a/libs/architectures/architectures/networks/wavenet.py +++ b/libs/architectures/architectures/networks/wavenet.py @@ -101,7 +101,7 @@ def __init__( self.init_conv = nn.Conv1d( in_channels, res_channels, kernel_size=2, dilation=1 ) - self.norm1 = norm_layer(res_channels) + self.norm1 = self.norm_layer(res_channels) self.layers_per_block = layers_per_block self.num_blocks = num_blocks self.res_channels = res_channels diff --git a/libs/architectures/poetry.lock b/libs/architectures/poetry.lock index b6fdf352..4a5faa1b 100644 --- a/libs/architectures/poetry.lock +++ b/libs/architectures/poetry.lock @@ -1,5 +1,30 @@ # This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. +[[package]] +name = "colorama" +version = "0.4.6" +description = "Cross-platform colored terminal text." +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" +files = [ + {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"}, + {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"}, +] + +[[package]] +name = "exceptiongroup" +version = "1.2.1" +description = "Backport of PEP 654 (exception groups)" +optional = false +python-versions = ">=3.7" +files = [ + {file = "exceptiongroup-1.2.1-py3-none-any.whl", hash = "sha256:5258b9ed329c5bbdd31a309f53cbfb0b155341807f6ff7606a1e801a891b29ad"}, + {file = "exceptiongroup-1.2.1.tar.gz", hash = "sha256:a4785e48b045528f5bfe627b6ad554ff32def154f42372786903b7abcfe1aa16"}, +] + +[package.extras] +test = ["pytest (>=6)"] + [[package]] name = "filelock" version = "3.14.0" @@ -103,6 +128,17 @@ docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.link perf = ["ipython"] testing = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-perf (>=0.9.2)", "pytest-ruff (>=0.2.1)"] +[[package]] +name = "iniconfig" +version = "2.0.0" +description = "brain-dead simple config-ini parsing" +optional = false +python-versions = ">=3.7" +files = [ + {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"}, + {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"}, +] + [[package]] name = "intel-openmp" version = "2021.4.0" @@ -436,6 +472,54 @@ files = [ {file = "nvidia_nvtx_cu11-11.8.86-py3-none-win_amd64.whl", hash = "sha256:54031010ee38d774b2991004d88f90bbd7bbc1458a96bbc4b42662756508c252"}, ] +[[package]] +name = "packaging" +version = "24.0" +description = "Core utilities for Python packages" +optional = false +python-versions = ">=3.7" +files = [ + {file = "packaging-24.0-py3-none-any.whl", hash = "sha256:2ddfb553fdf02fb784c234c7ba6ccc288296ceabec964ad2eae3777778130bc5"}, + {file = "packaging-24.0.tar.gz", hash = "sha256:eb82c5e3e56209074766e6885bb04b8c38a0c015d0a30036ebe7ece34c9989e9"}, +] + +[[package]] +name = "pluggy" +version = "1.5.0" +description = "plugin and hook calling mechanisms for python" +optional = false +python-versions = ">=3.8" +files = [ + {file = "pluggy-1.5.0-py3-none-any.whl", hash = "sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669"}, + {file = "pluggy-1.5.0.tar.gz", hash = "sha256:2cffa88e94fdc978c4c574f15f9e59b7f4201d439195c3715ca9e2486f1d0cf1"}, +] + +[package.extras] +dev = ["pre-commit", "tox"] +testing = ["pytest", "pytest-benchmark"] + +[[package]] +name = "pytest" +version = "8.2.1" +description = "pytest: simple powerful testing with Python" +optional = false +python-versions = ">=3.8" +files = [ + {file = "pytest-8.2.1-py3-none-any.whl", hash = "sha256:faccc5d332b8c3719f40283d0d44aa5cf101cec36f88cde9ed8f2bc0538612b1"}, + {file = "pytest-8.2.1.tar.gz", hash = "sha256:5046e5b46d8e4cac199c373041f26be56fdb81eb4e67dc11d4e10811fc3408fd"}, +] + +[package.dependencies] +colorama = {version = "*", markers = "sys_platform == \"win32\""} +exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""} +iniconfig = "*" +packaging = "*" +pluggy = ">=1.5,<2.0" +tomli = {version = ">=1", markers = "python_version < \"3.11\""} + +[package.extras] +dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"] + [[package]] name = "sympy" version = "1.12" @@ -463,6 +547,17 @@ files = [ {file = "tbb-2021.12.0-py3-none-win_amd64.whl", hash = "sha256:fc2772d850229f2f3df85f1109c4844c495a2db7433d38200959ee9265b34789"}, ] +[[package]] +name = "tomli" +version = "2.0.1" +description = "A lil' TOML parser" +optional = false +python-versions = ">=3.7" +files = [ + {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"}, + {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"}, +] + [[package]] name = "torch" version = "2.3.0+cu118" @@ -625,4 +720,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.8,<3.11" -content-hash = "e713da4c67ad8a6de32dbdab7191106b2c135baba5e95e3a6e39bf6b8de337f8" +content-hash = "4dca7ba58a1f9ad929fb1f694ceee57251043c0333998dcf51c7904d6f9607ad" diff --git a/libs/architectures/pyproject.toml b/libs/architectures/pyproject.toml index d76c7217..4809c17a 100644 --- a/libs/architectures/pyproject.toml +++ b/libs/architectures/pyproject.toml @@ -17,6 +17,10 @@ url = "https://download.pytorch.org/whl/cu118" secondary = true default = false + +[tool.poetry.group.dev.dependencies] +pytest = "^8.2.1" + [build-system] requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" diff --git a/libs/architectures/tests/networks/test_wavenet.py b/libs/architectures/tests/networks/test_wavenet.py new file mode 100644 index 00000000..f709381f --- /dev/null +++ b/libs/architectures/tests/networks/test_wavenet.py @@ -0,0 +1,17 @@ +import torch +from architectures.networks import WaveNet + + +def test_wavenet(): + in_channels = 2 + arch = WaveNet( + in_channels, + res_channels=4, + layers_per_block=2, + num_blocks=2, + kernel_size=2, + ) + + data = torch.randn(512, in_channels, 1024) + x = arch(data) + assert x.shape == (512, 1) diff --git a/libs/ledger/tests/test_injections.py b/libs/ledger/tests/test_injections.py index 2a5b1dd6..c3ae7b22 100644 --- a/libs/ledger/tests/test_injections.py +++ b/libs/ledger/tests/test_injections.py @@ -41,6 +41,7 @@ def ligo_response_set(self, duration, sample_rate, N): sample_rate=sample_rate, duration=duration, num_injections=N, + coalescence_time=duration / 2, **kwargs, ) assert str(exc.value).startswith("Specified waveform duration") @@ -53,6 +54,7 @@ def ligo_response_set(self, duration, sample_rate, N): sample_rate=sample_rate, duration=duration, num_injections=N - 1, + coalescence_time=duration / 2, **kwargs, ) assert str(exc.value).startswith("LigoResponseSet") @@ -61,6 +63,7 @@ def ligo_response_set(self, duration, sample_rate, N): sample_rate=sample_rate, duration=duration, num_injections=N, + coalescence_time=duration / 2, **kwargs, ) @@ -166,6 +169,7 @@ def test_read_with_shifts(self, ligo_response_set, tmp_path, N): # now try with times ligo_response_set.injection_time = np.arange(N) % (N // 2) ligo_response_set.duration = 2 + ligo_response_set.coalescence_time = ligo_response_set.duration / 2 for ifo in "hl": key = f"{ifo}1" old = getattr(ligo_response_set, key) diff --git a/ml4gw b/ml4gw index 05b38cdd..74c13d56 160000 --- a/ml4gw +++ b/ml4gw @@ -1 +1 @@ -Subproject commit 05b38cdd868c5c71338c0977ac96f7369dfe545c +Subproject commit 74c13d562f6d36e29fbdbb9d4794b55412f59c8e diff --git a/poetry.lock b/poetry.lock index 69b10df7..18436385 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,89 +1,10 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. - [[package]] name = "aiohttp" version = "3.9.2" description = "Async http client/server framework (asyncio)" +category = "main" optional = false python-versions = 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{file = "json5-0.9.14.tar.gz", hash = "sha256:9ed66c3a6ca3510a976a9ef9b8c0787de24802724ab1860bc0153c7fdd589b02"}, -] [package.extras] dev = ["hypothesis"] @@ -1426,12 +877,9 @@ dev = ["hypothesis"] name = "jsonargparse" version = "4.27.3" description = "Implement minimal boilerplate CLIs derived from type hints and parse from command line, config files and environment variables." +category = "dev" optional = false python-versions = ">=3.7" -files = [ - {file = "jsonargparse-4.27.3-py3-none-any.whl", hash = "sha256:74c0f4ff60af074cc20b8693003cd16ccc249030980a131e7eca001d9f79ad1a"}, - {file = "jsonargparse-4.27.3.tar.gz", hash = "sha256:bd1ff04a47d55ec80f96210ac23ae441bbeab1dd1791a561aaaa1b795c3593a7"}, -] [package.dependencies] PyYAML = ">=3.13" @@ -1459,23 +907,17 @@ urls = ["requests (>=2.18.4)"] name = "jsonpointer" version = "2.4" description = "Identify specific nodes in a JSON document (RFC 6901)" +category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*" -files = [ - 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Install all the Jupyter components in one go." +category = "dev" optional = false python-versions = "*" -files = [ - {file = "jupyter-1.0.0-py2.py3-none-any.whl", hash = "sha256:5b290f93b98ffbc21c0c7e749f054b3267782166d72fa5e3ed1ed4eaf34a2b78"}, - {file = "jupyter-1.0.0.tar.gz", hash = "sha256:d9dc4b3318f310e34c82951ea5d6683f67bed7def4b259fafbfe4f1beb1d8e5f"}, - {file = "jupyter-1.0.0.zip", hash = "sha256:3e1f86076bbb7c8c207829390305a2b1fe836d471ed54be66a3b8c41e7f46cc7"}, -] [package.dependencies] ipykernel = "*" @@ -1533,16 +968,13 @@ qtconsole = "*" name = "jupyter-client" version = "8.6.0" description = "Jupyter protocol implementation and client libraries" +category = "dev" optional = false python-versions = ">=3.8" -files = [ - {file = "jupyter_client-8.6.0-py3-none-any.whl", hash = "sha256:909c474dbe62582ae62b758bca86d6518c85234bdee2d908c778db6d72f39d99"}, - {file = "jupyter_client-8.6.0.tar.gz", hash = "sha256:0642244bb83b4764ae60d07e010e15f0e2d275ec4e918a8f7b80fbbef3ca60c7"}, -] [package.dependencies] importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""} -jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0" +jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" python-dateutil = ">=2.8.2" pyzmq = ">=23.0" tornado = ">=6.2" @@ -1556,18 +988,15 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt name = "jupyter-console" version = "6.6.3" description = "Jupyter terminal console" +category = "dev" optional = false python-versions = ">=3.7" -files = [ - {file = "jupyter_console-6.6.3-py3-none-any.whl", hash = "sha256:309d33409fcc92ffdad25f0bcdf9a4a9daa61b6f341177570fdac03de5352485"}, - {file = "jupyter_console-6.6.3.tar.gz", hash = "sha256:566a4bf31c87adbfadf22cdf846e3069b59a71ed5da71d6ba4d8aaad14a53539"}, -] [package.dependencies] ipykernel = ">=6.14" ipython = "*" jupyter-client = ">=7.0.0" -jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0" +jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" prompt-toolkit = ">=3.0.30" pygments = "*" pyzmq = ">=17" @@ -1580,12 +1009,9 @@ test = ["flaky", "pexpect", "pytest"] name = "jupyter-core" version = "5.7.1" description = "Jupyter core package. A base package on which Jupyter projects rely." +category = "dev" optional = false python-versions = ">=3.8" -files = [ - {file = "jupyter_core-5.7.1-py3-none-any.whl", hash = "sha256:c65c82126453a723a2804aa52409930434598fd9d35091d63dfb919d2b765bb7"}, - {file = "jupyter_core-5.7.1.tar.gz", hash = "sha256:de61a9d7fc71240f688b2fb5ab659fbb56979458dc66a71decd098e03c79e218"}, -] [package.dependencies] platformdirs = ">=2.5" @@ -1600,12 +1026,9 @@ test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"] name = "jupyter-events" version = "0.9.0" description = "Jupyter Event System library" +category = "dev" optional = false python-versions = ">=3.8" -files = [ - {file = "jupyter_events-0.9.0-py3-none-any.whl", hash = "sha256:d853b3c10273ff9bc8bb8b30076d65e2c9685579db736873de6c2232dde148bf"}, - {file = "jupyter_events-0.9.0.tar.gz", hash = "sha256:81ad2e4bc710881ec274d31c6c50669d71bbaa5dd9d01e600b56faa85700d399"}, -] [package.dependencies] jsonschema = {version = ">=4.18.0", extras = ["format-nongpl"]} @@ -1625,12 +1048,9 @@ test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "p name = "jupyter-lsp" version = "2.2.2" description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server" +category = "dev" optional = false python-versions = ">=3.8" -files = [ - 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"pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"] +docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] +testing = ["big-O", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<3.11" -content-hash = "e1a6b50e08664ce026827d9a5bb616c89a115d5717c0e915b66b27e87cfb4a29" +content-hash = "2329d99c3002c8d567cc0025ccf7179b68009a3843ee00fef5bd92662773cbab" diff --git a/projects/data/pyproject.toml b/projects/data/pyproject.toml index fc9a343c..f682d146 100644 --- a/projects/data/pyproject.toml +++ b/projects/data/pyproject.toml @@ -16,6 +16,9 @@ priors = {path = "../../libs/priors", develop = true} ml4gw = {path = "../../ml4gw", develop = true} aframe = {path = "../..", develop = true} +[tool.poetry.group.dev.dependencies] +pytest = "^8.2.1" + [build-system] requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" diff --git a/projects/data/tests/waveforms/test_injection.py b/projects/data/tests/waveforms/test_injection.py new file mode 100644 index 00000000..cfc413c0 --- /dev/null +++ b/projects/data/tests/waveforms/test_injection.py @@ -0,0 +1,11 @@ +import pytest +from data.waveforms.injection import WaveformGenerator + + +@pytest.fixture +def waveform_generator(): + return WaveformGenerator(waveform_duration=1.0, sample_rate=4096) + + +def test_waveform_size(waveform_generator): + assert waveform_generator.waveform_size == 4096 diff --git a/projects/export/apptainer.def b/projects/export/apptainer.def index c293f565..4a6f6021 100644 --- a/projects/export/apptainer.def +++ b/projects/export/apptainer.def @@ -33,6 +33,9 @@ Stage: final /opt/aframe /opt/aframe %post +# install pytest so we can run +# unit tests during CI inside container cd /opt/aframe/projects/export pip install -r requirements.txt --no-deps --no-cache-dir pip install -e . --no-deps --no-cache-dir +pip install pytest diff --git a/projects/export/export/main.py b/projects/export/export/main.py index b80c8254..8fd27081 100644 --- a/projects/export/export/main.py +++ b/projects/export/export/main.py @@ -23,7 +23,7 @@ def scale_model(model, instances): def open_file(path, mode="rb"): - if path.startswith("s3://"): + if str(path).startswith("s3://"): fs = s3fs.S3FileSystem() return fs.open(path, mode) else: diff --git a/projects/export/poetry.lock b/projects/export/poetry.lock index ad768b4c..1b856076 100644 --- a/projects/export/poetry.lock +++ b/projects/export/poetry.lock @@ -1,12 +1,10 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. - [[package]] name = "aframe" version = "0.0.1" description = "End-to-end aframe pipeline components" +category = "main" optional = false python-versions = ">=3.9,<3.11" -files = 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Install all the Jupyter components in one go." +category = "main" optional = false python-versions = "*" -files = [ - {file = "jupyter-1.0.0-py2.py3-none-any.whl", hash = "sha256:5b290f93b98ffbc21c0c7e749f054b3267782166d72fa5e3ed1ed4eaf34a2b78"}, - {file = "jupyter-1.0.0.tar.gz", hash = "sha256:d9dc4b3318f310e34c82951ea5d6683f67bed7def4b259fafbfe4f1beb1d8e5f"}, - {file = "jupyter-1.0.0.zip", hash = "sha256:3e1f86076bbb7c8c207829390305a2b1fe836d471ed54be66a3b8c41e7f46cc7"}, -] [package.dependencies] ipykernel = "*" @@ -1799,16 +912,13 @@ qtconsole = "*" name = "jupyter-client" version = "8.6.0" description = "Jupyter protocol implementation and client libraries" +category = "main" optional = false python-versions = ">=3.8" -files = [ - {file = "jupyter_client-8.6.0-py3-none-any.whl", hash = "sha256:909c474dbe62582ae62b758bca86d6518c85234bdee2d908c778db6d72f39d99"}, - {file = "jupyter_client-8.6.0.tar.gz", hash = "sha256:0642244bb83b4764ae60d07e010e15f0e2d275ec4e918a8f7b80fbbef3ca60c7"}, -] [package.dependencies] importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""} -jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0" +jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" python-dateutil = ">=2.8.2" pyzmq = ">=23.0" tornado = ">=6.2" @@ -1822,18 +932,15 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt name = "jupyter-console" version = "6.6.3" description = "Jupyter terminal console" +category = "main" optional = false python-versions = ">=3.7" -files = [ - {file = "jupyter_console-6.6.3-py3-none-any.whl", hash = "sha256:309d33409fcc92ffdad25f0bcdf9a4a9daa61b6f341177570fdac03de5352485"}, - {file = "jupyter_console-6.6.3.tar.gz", hash = "sha256:566a4bf31c87adbfadf22cdf846e3069b59a71ed5da71d6ba4d8aaad14a53539"}, -] [package.dependencies] ipykernel = ">=6.14" ipython = "*" jupyter-client = ">=7.0.0" -jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0" +jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" prompt-toolkit = ">=3.0.30" pygments = "*" pyzmq = ">=17" @@ -1846,12 +953,9 @@ test = ["flaky", "pexpect", "pytest"] name = "jupyter-core" version = "5.7.1" description = "Jupyter core package. A base package on which Jupyter projects rely." +category = "main" optional = false python-versions = ">=3.8" -files = [ - {file = "jupyter_core-5.7.1-py3-none-any.whl", hash = "sha256:c65c82126453a723a2804aa52409930434598fd9d35091d63dfb919d2b765bb7"}, - {file = "jupyter_core-5.7.1.tar.gz", hash = "sha256:de61a9d7fc71240f688b2fb5ab659fbb56979458dc66a71decd098e03c79e218"}, -] [package.dependencies] platformdirs = ">=2.5" @@ -1866,12 +970,9 @@ test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"] name = "jupyter-events" version = "0.9.0" description = "Jupyter Event System library" +category = "main" optional = false python-versions = ">=3.8" -files = [ - {file = "jupyter_events-0.9.0-py3-none-any.whl", hash = "sha256:d853b3c10273ff9bc8bb8b30076d65e2c9685579db736873de6c2232dde148bf"}, - {file = "jupyter_events-0.9.0.tar.gz", hash = "sha256:81ad2e4bc710881ec274d31c6c50669d71bbaa5dd9d01e600b56faa85700d399"}, -] [package.dependencies] jsonschema = {version = ">=4.18.0", extras = ["format-nongpl"]} @@ -1891,12 +992,9 @@ test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "p name = "jupyter-lsp" version = "2.2.2" description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server" +category = "main" optional = false python-versions = ">=3.8" -files = [ - 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-[package.dependencies] -setuptools = "*" - -[package.extras] -docs = ["Sphinx", "repoze.sphinx.autointerface", "sphinx-rtd-theme"] -test = ["coverage (>=5.0.3)", "zope.event", "zope.testing"] -testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"] - -[metadata] -lock-version = "2.0" -python-versions = ">=3.9,<3.11" -content-hash = "2bc4bb4039abca681d0d2e17f04f79e3502d72ce44511b1e9d7a46919df3077a" diff --git a/projects/export/pyproject.toml b/projects/export/pyproject.toml index efa40ad6..92c5f9ad 100644 --- a/projects/export/pyproject.toml +++ b/projects/export/pyproject.toml @@ -40,6 +40,11 @@ urllib3 = ">=1.25.4,<1.27" name = "torch" url = "https://download.pytorch.org/whl/cpu" + +[tool.poetry.group.dev.dependencies] +pytest = "^8.2.1" + + [build-system] requires = ["poetry-core"] build-backend = "poetry.core.masonry.api" diff --git a/projects/export/tests/test_export.py b/projects/export/tests/test_export.py new file mode 100644 index 00000000..cdefe9a6 --- /dev/null +++ b/projects/export/tests/test_export.py @@ -0,0 +1,520 @@ +import re +import shutil +from contextlib import nullcontext +from pathlib import Path + +import h5py +import numpy as np +import pytest +import torch +from export.main import export +from google.protobuf import text_format +from tritonclient.grpc.model_config_pb2 import ModelConfig + +import hermes.quiver as qv +from ml4gw.nn.resnet import ResNet1D + + +# set up a directory for the entirety of the session +# which will store all the weight values of each +# NN we need to create in response to a particular +# num_ifos/sample_rate/kernel_length combination +@pytest.fixture(scope="session") +def weights_dir(): + weights_dir = Path(__file__).resolve().parent / "weights" + weights_dir.mkdir(exist_ok=True, parents=True) + yield weights_dir + shutil.rmtree(weights_dir) + + +@pytest.fixture +def batch_file(tmp_path, batch_size, num_ifos, sample_rate, kernel_length): + data = np.random.randn(batch_size, num_ifos, sample_rate * kernel_length) + file = tmp_path / "batch_file.h5" + with h5py.File(file, "w") as f: + f.create_dataset("X", data=data) + return file + + +@pytest.fixture +def platform(): + return qv.Platform.ONNX + + +# only create a new neural network if the weights for +# a network of this num_ifos/sample_rate/kernel_length +# combination has not yet been created. Otherwise just +# return the path to those weights as-is +@pytest.fixture +def architecture(): + return lambda num_ifos: ResNet1D(num_ifos, layers=[2, 2], classes=1) + + +@pytest.fixture +def trace_network_weights(weights_dir, architecture): + def fn(num_ifos, target, sample_rate, kernel_length, batch_size): + sample_input = torch.randn( + batch_size, num_ifos, sample_rate * kernel_length + ) + weights = weights_dir / f"{num_ifos}-{sample_rate}-{kernel_length}.pt" + if not weights.exists(): + aframe = architecture(num_ifos) + trace = torch.jit.trace(aframe, sample_input) + with open(weights, "wb") as f: + torch.jit.save(trace, f) + + shutil.copy(weights, target) + + return fn + + +@pytest.fixture +def repo_dir(tmp_path): + repo = tmp_path / "repo" + repo.mkdir() + return repo + + +@pytest.fixture +def output_dir(tmp_path): + output_dir = tmp_path / "output" + output_dir.mkdir() + return output_dir + + +@pytest.fixture +def fduration(): + return 1 + + +def load_config(config_path: Path): + config = ModelConfig() + text_format.Merge(config_path.read_text(), config) + return config + + +@pytest.fixture +def validate_repo(repo_dir): + def fn( + expected_aframe_instances, + expected_snapshots, + expected_versions, + expected_num_ifos, + expected_stream_size, + expected_state_size, + expected_aframe_size, + expected_crop, + expected_batch_size, + ): + for i, model in enumerate(repo_dir.iterdir()): + config = load_config(model / "config.pbtxt") + if model.name == "snapshotter": + try: + instance_group = config.instance_group[0] + except IndexError: + if expected_snapshots is not None: + raise ValueError( + "No instance group but expected snapshots " + f"is {expected_snapshots}" + ) + else: + if expected_snapshots is None: + raise ValueError( + "Didn't expect snapshots but found " + f"instance group {instance_group}" + ) + assert instance_group.count == expected_snapshots + + # we now pass two streams: + # one is used to whiten the other + assert config.input[0].dims == [ + 2, + expected_num_ifos, + expected_stream_size * expected_batch_size, + ] + assert config.output[0].dims == [ + 2, + expected_num_ifos, + expected_state_size + + (expected_stream_size * expected_batch_size), + ] + + assert (model / "1" / "model.onnx").exists() + assert not (model / "2").is_dir() + elif model.name == "aframe": + expected_instances = expected_aframe_instances + expected_output_shape = [expected_batch_size, 1] + assert config.optimization.graph.level == -1 + + try: + instance_group = config.instance_group[0] + except IndexError: + if expected_instances is not None: + raise ValueError( + "No instance group but expected instances " + f"is {expected_instances}" + ) + else: + if expected_instances is None: + raise ValueError( + "Didn't expect aframe instances but found " + f"instance group {instance_group}" + ) + assert instance_group.count == expected_instances + + assert config.input[0].dims == [ + expected_batch_size, + expected_num_ifos, + expected_aframe_size, + ] + assert config.output[0].dims == expected_output_shape + + if isinstance(expected_versions, tuple): + idx = 0 + versions = expected_versions[idx] + else: + versions = expected_versions + + for j in range(versions): + assert (model / str(j + 1) / "model.onnx").is_file() + assert not (model / str(j + 2)).is_dir() + + elif model.name == "aframe-stream": + assert (model / "1").is_dir() + assert not (model / "2").is_dir() + elif model.name == "preprocessor": + assert config.input[0].dims == [ + 2, + expected_num_ifos, + expected_state_size + + (expected_stream_size * expected_batch_size), + ] + assert config.output[0].dims == [ + expected_batch_size, + expected_num_ifos, + expected_aframe_size, + ] + else: + raise ValueError(f"Unexpected model {model.name} in repo") + + assert i == 3, f"Wrong number of models {i + 1}" + + return fn + + +# first set of tests will check that all the properties +# of the inputs to the neural network get set up properly +@pytest.fixture +def num_ifos(): + return 2 + + +@pytest.fixture +def sample_rate(): + return 128 + + +@pytest.fixture(params=[1, 4, 8]) +def inference_sampling_rate(request): + return request.param + + +@pytest.fixture(params=[2, 4]) +def kernel_length(request): + return request.param + + +@pytest.fixture(params=[8, 16]) +def psd_length(request): + return request.param + + +@pytest.fixture(params=[1, 2, 8]) +def batch_size(request): + return request.param + + +def test_export_for_shapes( + repo_dir, + batch_file, + num_ifos, + sample_rate, + kernel_length, + psd_length, + batch_size, + inference_sampling_rate, + trace_network_weights, + validate_repo, + output_dir, + platform, +): + weights = output_dir / "weights.pt" + trace_network_weights( + num_ifos, weights, sample_rate, kernel_length, batch_size + ) + + # test fully from scratch behavior + if (kernel_length * inference_sampling_rate) <= 1: + context = pytest.raises(ValueError) + else: + context = nullcontext() + + fduration = 1 + expected_state_size = int( + sample_rate + * ( + kernel_length + + fduration + + psd_length + - (1 / inference_sampling_rate) + ) + ) + with context: + export( + weights, + str(repo_dir), + batch_file, + num_ifos=num_ifos, + inference_sampling_rate=inference_sampling_rate, + kernel_length=kernel_length, + psd_length=psd_length, + sample_rate=sample_rate, + batch_size=batch_size, + fduration=fduration, + streams_per_gpu=1, + aframe_instances=1, + platform=platform, + ) + validate_repo( + expected_aframe_instances=1, + expected_snapshots=1, + expected_versions=1, + expected_num_ifos=num_ifos, + expected_stream_size=int(sample_rate / inference_sampling_rate), + expected_state_size=expected_state_size, + expected_aframe_size=int(sample_rate * kernel_length), + expected_crop=int(sample_rate * fduration), + expected_batch_size=batch_size, + ) + + +def test_export_for_weights( + repo_dir, + output_dir, + num_ifos, + kernel_length, + sample_rate, + psd_length, + inference_sampling_rate, + fduration, + trace_network_weights, + validate_repo, + batch_size, + batch_file, + platform, +): + weights = output_dir / "weights.pt" + trace_network_weights( + num_ifos, weights, sample_rate, kernel_length, batch_size + ) + + expected_state_size = int( + sample_rate + * ( + kernel_length + + fduration + + psd_length + - (1 / inference_sampling_rate) + ) + ) + export( + weights, + str(repo_dir), + batch_file, + num_ifos=num_ifos, + inference_sampling_rate=inference_sampling_rate, + sample_rate=sample_rate, + kernel_length=kernel_length, + psd_length=psd_length, + batch_size=1, + fduration=fduration, + streams_per_gpu=1, + aframe_instances=1, + platform=platform, + ) + validate_repo( + expected_aframe_instances=1, + expected_snapshots=1, + expected_versions=1, + expected_num_ifos=num_ifos, + expected_stream_size=int(sample_rate / inference_sampling_rate), + expected_aframe_size=int(sample_rate * kernel_length), + expected_state_size=expected_state_size, + expected_crop=int(sample_rate), + expected_batch_size=1, + ) + + +# now test how different values of scaling parameters +# lead to different configs +@pytest.fixture(params=[None, 1]) +def aframe_instances(request): + return request.param + + +@pytest.fixture(params=[None, 1]) +def preproc_instances(request): + return request.param + + +@pytest.fixture(params=[1, 4]) +def streams_per_gpu(request): + return request.param + + +# indicates whether we ought to delete the contents +# of the model repository before doing export +@pytest.fixture(params=[True, False]) +def clean(request): + return request.param + + +def test_export_for_scaling( + output_dir, + repo_dir, + batch_file, + streams_per_gpu, + aframe_instances, + preproc_instances, + clean, + num_ifos, + kernel_length, + sample_rate, + psd_length, + inference_sampling_rate, + fduration, + validate_repo, + trace_network_weights, + batch_size, + platform, +): + weights = output_dir / "weights.pt" + trace_network_weights( + num_ifos, weights, sample_rate, kernel_length, batch_size + ) + expected_state_size = int( + sample_rate + * ( + kernel_length + + fduration + + psd_length + - (1 / inference_sampling_rate) + ) + ) + + if clean: + p = repo_dir / "dummy_file.txt" + p.write_text("dummy text") + + def run_export( + aframe_instances=aframe_instances, + preproc_instances=preproc_instances, + clean=clean, + ): + export( + weights, + str(repo_dir), + batch_file, + num_ifos=num_ifos, + inference_sampling_rate=inference_sampling_rate, + sample_rate=sample_rate, + kernel_length=kernel_length, + psd_length=psd_length, + batch_size=1, + fduration=1, + streams_per_gpu=streams_per_gpu, + aframe_instances=aframe_instances, + clean=clean, + platform=platform, + ) + + run_export() + validate_repo( + expected_aframe_instances=aframe_instances, + expected_snapshots=streams_per_gpu, + expected_versions=1, + expected_num_ifos=num_ifos, + expected_stream_size=int(sample_rate / inference_sampling_rate), + expected_aframe_size=int(sample_rate * kernel_length), + expected_state_size=expected_state_size, + expected_crop=int(sample_rate), + expected_batch_size=1, + ) + + # now check what happens if the repo already exists + run_export() + validate_repo( + expected_aframe_instances=aframe_instances, + expected_snapshots=streams_per_gpu, + expected_versions=1 if clean else 2, + expected_num_ifos=num_ifos, + expected_stream_size=int(sample_rate / inference_sampling_rate), + expected_aframe_size=int(sample_rate * kernel_length), + expected_state_size=expected_state_size, + expected_crop=int(sample_rate), + expected_batch_size=1, + ) + + # now make sure if we change the scale + # we get another version and the config changes + run_export( + aframe_instances=3, preproc_instances=preproc_instances, clean=False + ) + validate_repo( + expected_aframe_instances=3, + expected_snapshots=streams_per_gpu, + expected_versions=2 if clean else 3, + expected_num_ifos=num_ifos, + expected_stream_size=int(sample_rate / inference_sampling_rate), + expected_aframe_size=int(sample_rate * kernel_length), + expected_state_size=expected_state_size, + expected_batch_size=1, + expected_crop=int(sample_rate), + ) + + # now test to make sure an error gets raised if the + # ensemble already exists but aframe is not part of it + shutil.move(repo_dir / "aframe", repo_dir / "aaframe") + aframe_config = repo_dir / "aaframe" / "config.pbtxt" + config = aframe_config.read_text() + config = re.sub('name: "aframe"', 'name: "aaframe"', config) + aframe_config.write_text(config) + + ensemble_config = repo_dir / "aframe-stream" / "config.pbtxt" + config = ensemble_config.read_text() + config = re.sub('model_name: "aframe"', 'model_name: "aaframe"', config) + ensemble_config.write_text(config) + + with pytest.raises(ValueError) as exc_info: + run_export(clean=False) + assert str(exc_info.value).endswith("model 'aframe'") + + # ensure that aframe got exported before things + # went wrong with the ensemble. TODO: this is + # actually probably undesirable behavior, but I'm + # not sure the best way to handle it elegantly in + # the export function. I guess a try-catch on the + # ensemble section that deletes the most recent + # aframe version if things go wrong? + shutil.rmtree(repo_dir / "aaframe") + validate_repo( + expected_aframe_instances=aframe_instances, + expected_snapshots=streams_per_gpu, + expected_versions=(1, 3) if clean else (1, 4), + expected_num_ifos=num_ifos, + expected_stream_size=int(sample_rate / inference_sampling_rate), + expected_aframe_size=int(sample_rate * kernel_length), + expected_state_size=expected_state_size, + expected_batch_size=1, + expected_crop=int(sample_rate), + ) diff --git a/projects/infer/apptainer.def b/projects/infer/apptainer.def new file mode 100644 index 00000000..7be2c6fd --- /dev/null +++ b/projects/infer/apptainer.def @@ -0,0 +1,46 @@ +Bootstrap: docker +From: python:3.10.12-slim-bullseye +Stage: build + +%files +# only copy precisely the files we need to keep things +# light and protect against any large files that might +# accidentally get created in this repo +. /opt/aframe/projects/infer +../utils /opt/aframe/projects/utils +../../aframe /opt/aframe/aframe +../../pyproject.toml /opt/aframe/pyproject.toml +../../hermes /opt/aframe/hermes +../../ml4gw /opt/aframe/ml4gw +../../libs/ledger /opt/aframe/libs/ledger +../../pycondor /opt/aframe/pycondor + +%post +# installing the local package editably via pip +# works, but none of the dependencies (e.g. ml4gw) +# are installed editably, so we'll opt for using +# the full poetry machinery without using a +# virtual environment. Note that this can potentially +# cause issues if the poetry install makes changes to +# the virtualenv package in the base environment, so +# we'll hard pin it to the value we need. +# TODO: there's got to be a better solution here +python -m pip install poetry==1.7.1 +cd /opt/aframe/projects/infer +poetry export -o requirements.txt --without-hashes \ + && sed -i 's|\(.*\) @ file://|-e |' requirements.txt + +Bootstrap: docker +From: python:3.10.12-slim-bullseye +Stage: final + +%files from build +/opt/aframe /opt/aframe + +%post +# install pytest so we can run unittests +# inside the container during CI +cd /opt/aframe/projects/infer +pip install -r requirements.txt --no-deps --no-cache-dir +pip install -e . --no-deps --no-cache-dir +pip install pytest diff --git a/projects/infer/poetry.lock b/projects/infer/poetry.lock index 3cba2dbc..b675f3d3 100644 --- a/projects/infer/poetry.lock +++ b/projects/infer/poetry.lock @@ -1,12 +1,10 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. - 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Install all the Jupyter components in one go." +category = "main" optional = false python-versions = "*" -files = [ - {file = "jupyter-1.0.0-py2.py3-none-any.whl", hash = "sha256:5b290f93b98ffbc21c0c7e749f054b3267782166d72fa5e3ed1ed4eaf34a2b78"}, - {file = "jupyter-1.0.0.tar.gz", hash = "sha256:d9dc4b3318f310e34c82951ea5d6683f67bed7def4b259fafbfe4f1beb1d8e5f"}, - {file = "jupyter-1.0.0.zip", hash = "sha256:3e1f86076bbb7c8c207829390305a2b1fe836d471ed54be66a3b8c41e7f46cc7"}, -] [package.dependencies] ipykernel = "*" @@ -2005,16 +1003,13 @@ qtconsole = "*" name = "jupyter-client" version = "8.6.1" description = "Jupyter protocol implementation and client libraries" +category = "main" optional = false python-versions = ">=3.8" -files = [ - {file = "jupyter_client-8.6.1-py3-none-any.whl", hash = "sha256:3b7bd22f058434e3b9a7ea4b1500ed47de2713872288c0d511d19926f99b459f"}, - {file = "jupyter_client-8.6.1.tar.gz", hash = "sha256:e842515e2bab8e19186d89fdfea7abd15e39dd581f94e399f00e2af5a1652d3f"}, -] [package.dependencies] importlib-metadata = {version = ">=4.8.3", markers = "python_version < \"3.10\""} -jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0" +jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" python-dateutil = ">=2.8.2" pyzmq = ">=23.0" tornado = ">=6.2" @@ -2028,230 +1023,2589 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt name = "jupyter-console" version = "6.6.3" description = "Jupyter terminal console" +category = "main" optional = false python-versions = ">=3.7" -files = [ + +[package.dependencies] +ipykernel = ">=6.14" +ipython = "*" +jupyter-client = ">=7.0.0" +jupyter-core = ">=4.12,<5.0.0 || >=5.1.0" +prompt-toolkit = ">=3.0.30" +pygments = "*" +pyzmq = ">=17" +traitlets = ">=5.4" + +[package.extras] +test = ["flaky", "pexpect", "pytest"] + +[[package]] +name = "jupyter-core" +version = "5.7.2" +description = "Jupyter core package. 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-[package.dependencies] -setuptools = "*" - -[package.extras] -docs = ["Sphinx", "repoze.sphinx.autointerface", "sphinx-rtd-theme"] -test = ["coverage (>=5.0.3)", "zope.event", "zope.testing"] -testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"] - -[metadata] -lock-version = "2.0" -python-versions = ">=3.9,<3.11" -content-hash = "19caec41fedb6d20aac64b71983493b9916a1ff9607d2d0e49e006c78e3e77e2" diff --git a/projects/infer/pyproject.toml b/projects/infer/pyproject.toml index 55dd178f..7f92a52c 100644 --- a/projects/infer/pyproject.toml +++ b/projects/infer/pyproject.toml @@ -14,12 +14,15 @@ ray = "^2.6" jsonargparse = "^4.24" tqdm = "^4.66" -ml4gw-hermes = {path = "../../hermes", develop = true, extras = ["serve"]} +ml4gw-hermes = {path = "../../hermes", develop = true, extras = ["serve", "torch"]} utils = {path = "../utils", develop = true} aframe = {path = "../../", develop = true} ledger = {path = "../../libs/ledger", develop = true} pycondor = {path = "../../pycondor", develop = true} +# workaround for: https://github.com/python-poetry/poetry-plugin-export/issues/183 +urllib3 = ">=1.25.4,<1.27" + [tool.poetry.group.dev.dependencies] jupyter = "^1.0.0" pytest = "^7.3" diff --git a/projects/infer/tests/test_postprocess.py b/projects/infer/tests/test_postprocess.py new file mode 100644 index 00000000..bf7b3751 --- /dev/null +++ b/projects/infer/tests/test_postprocess.py @@ -0,0 +1,14 @@ +from infer.postprocess import Postprocessor + + +def test_postprocessor(): + postprocessor = Postprocessor( + t0=0.0, + shifts=[0.1, 0.2, 0.3], + psd_length=10.0, + fduration=1.0, + inference_sampling_rate=100.0, + integration_window_length=0.5, + cluster_window_length=0.2, + ) + assert postprocessor.t0 == 9.0 diff --git a/projects/train/apptainer.def b/projects/train/apptainer.def index 9735b6a4..b50c0607 100644 --- a/projects/train/apptainer.def +++ b/projects/train/apptainer.def @@ -37,14 +37,9 @@ Stage: final /opt/aframe /opt/aframe %post -# need git to install ray-kube -# TODO: longer term, this should probably just -# a submodule of this project -apt-get update -apt-get install -y --no-install-recommends git -apt-get clean - - +# install pytest so we can run unit tests +# inside container during CI cd /opt/aframe/projects/train pip install -r requirements.txt --no-deps --no-cache-dir pip install -e . --no-deps --no-cache-dir +pip install pytest diff --git a/projects/train/tests/test_augmentations.py b/projects/train/tests/test_augmentations.py new file mode 100644 index 00000000..15146b73 --- /dev/null +++ b/projects/train/tests/test_augmentations.py @@ -0,0 +1,116 @@ +from unittest.mock import patch + +import numpy as np +import pytest +import torch + +from train.augmentations import ChannelSwapper + + +@pytest.fixture +def sample_rate(): + return 512 + + +@pytest.fixture(params=[0, 0.25, 1]) +def prob(request): + return request.param + + +@pytest.fixture(params=[0.0, 0.25, 0.5, 1]) +def flip_prob(request): + return request.param + + +@pytest.fixture +def rvs(): + return torch.Tensor([[0.0, 0.49], [0.51, 0.1], [0.9, 0.2], [0.1, 0.3]]) + + +@pytest.fixture +def true_idx(flip_prob): + if flip_prob in (0, 1): + idx = [k for i in range(4) for k in [[i, j] for j in range(2)]] + if flip_prob: + neg_idx = idx + pos_idx = [] + else: + pos_idx = idx + neg_idx = [] + else: + if flip_prob == 0.5: + neg_idx = [ + [0, 0], + [0, 1], + [1, 1], + [2, 1], + [3, 0], + [3, 1], + ] + pos_idx = [ + [1, 0], + [2, 0], + ] + else: + neg_idx = [[0, 0], [1, 1], [2, 1], [3, 0]] + pos_idx = [ + [0, 1], + [1, 0], + [2, 0], + [3, 1], + ] + + return neg_idx, pos_idx + + +def validate_augmenters(X, idx, true, false, prob): + neg_idx, pos_idx = idx + if neg_idx: + neg0, neg1 = zip(*neg_idx) + assert (X[neg0, neg1] == true).all() + elif prob != 0: + raise ValueError("Missing negative indices") + + if pos_idx: + pos0, pos1 = zip(*pos_idx) + assert (X[pos0, pos1] == false).all() + elif prob != 1: + raise ValueError("Missing positive indices") + + +@pytest.fixture(params=[0.5]) +def frac(): + return 0.5 + + +def test_channel_swapper(frac): + tform = ChannelSwapper(frac=frac) + n_batch = 128 + X = ( + torch.arange(n_batch) + .repeat(n_batch, 1) + .transpose(1, 0) + .reshape(n_batch, 2, -1) + ) + num = int(frac * n_batch) + num = num if not num % 2 else num - 1 + channels = torch.ones(num // 2, dtype=torch.long) + copy = torch.clone(X) + with patch("torch.randint", return_value=channels): + X, indices = tform(X) + + target_indices = torch.roll(indices, shifts=num // 2, dims=0) + X = X.cpu().numpy() + copy = copy.cpu().numpy() + indices = indices.cpu().numpy() + channels = channels.repeat(2) + + assert all(indices == np.arange(num)) + assert (X[indices, channels] == copy[target_indices, channels]).all() + + tform = ChannelSwapper(frac=0) + X = torch.arange(6).repeat(6, 1).transpose(1, 0).reshape(-1, 2, 6) + copy = torch.clone(X) + X, indices = tform(X) + assert not indices + assert (X == copy).all() diff --git a/projects/train/train/augmentations.py b/projects/train/train/augmentations.py index 63e44232..5d66ab9b 100644 --- a/projects/train/train/augmentations.py +++ b/projects/train/train/augmentations.py @@ -61,46 +61,6 @@ def forward(self, X): return X, indices -class SignalInverter(torch.nn.Module): - """ - Data augmentation that randomly inverts data in a kernel - - Args: - prob: - Probability that a kernel is inverted - """ - - def __init__(self, prob: float = 0.5): - super().__init__() - self.prob = prob - - def forward(self, X): - if self.training: - mask = torch.rand(size=X.shape[:-1]) < self.prob - X[mask] *= -1 - return X - - -class SignalReverser(torch.nn.Module): - """ - Data augmentation that randomly reverses data in a kernel - - Args: - prob: - Probability that a kernel is reversed - """ - - def __init__(self, prob: float = 0.5): - super().__init__() - self.prob = prob - - def forward(self, X): - if self.training: - mask = torch.rand(size=X.shape[:-1]) < self.prob - X[mask] = X[mask].flip(-1) - return X - - class SnrRescaler(torch.nn.Module): """ Module that calculates SNRs of injections relative diff --git a/projects/train/train/data/base.py b/projects/train/train/data/base.py index a7067dc2..40867b8a 100644 --- a/projects/train/train/data/base.py +++ b/projects/train/train/data/base.py @@ -11,6 +11,7 @@ import torch from ledger.injections import LigoWaveformSet +from ml4gw.augmentations import SignalInverter, SignalReverser from ml4gw.dataloading import Hdf5TimeSeriesDataset from ml4gw.transforms import Whiten from ml4gw.utils.slicing import unfold_windows @@ -86,8 +87,8 @@ def __init__( self.num_ifos = len(ifos) # Set up some of our data augmentation modules - self.inverter = aug.SignalInverter(0.5) - self.reverser = aug.SignalReverser(0.5) + self.inverter = SignalInverter(0.5) + self.reverser = SignalReverser(0.5) # these are modules that require our data to be # downloaded first, either for loading signals