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Updated some Descriptions
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lapplislazuli committed Mar 27, 2022
1 parent 2c2b991 commit 9a2418b
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Showing 8 changed files with 11 additions and 13 deletions.
2 changes: 1 addition & 1 deletion Dockerfile
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FROM nvcr.io/nvidia/pytorch:20.01-py3

LABEL maintainer="L.H.Applis@tu-delft.nl"
LABEL maintainer="L.H.Applis@tudelft.nl"
LABEL name="ciselab/codebert-code2text"
LABEL url="https://github.com/ciselab/CodeBert-CodeToText-Reproduction"
LABEL vcs="https://github.com/ciselab/CodeBert-CodeToText-Reproduction"
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2 changes: 1 addition & 1 deletion LICENSE
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MIT License

Copyright (c) 2020 CISELab
Copyright (c) 2022 CISELab

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
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4 changes: 1 addition & 3 deletions README.md
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Expand Up @@ -24,8 +24,6 @@ You can build the docker file beforehand using
docker build . -t ciselab/codebert-code2text:1.3 -t ciselab/codebert-code2text:latest
```

Or you can comment-in the build parts in the docker-compose.yml

Run the experiment using

```
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In comparison, training on a RTX 1070 took 7h per epoch.
Training on a 3080ti took 6h per epoch.
Training on an A40 took ~4h per epoch. In general, GPU tries to allocate around 12gb of memory.
Training on an A40 took ~4h per epoch. In general, the GPU tries to allocate around 12gb of memory.

In general, despite being a good first step, GPU Containers turned out to be quite fragile.
We have seen multiple problems with Framework-Versions, Hardware and OS combinations.
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2 changes: 1 addition & 1 deletion changes.md
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Expand Up @@ -13,7 +13,7 @@ this file holds the changes applied to the existing project from CodeXGlue
---------


- Moved to Cuda Container, removed conda environment.yml in favour of pip requirements.txt
- Moved to Cuda Container, removed conda environment.yml in Docker in favour of pip requirements.txt
- Added a lot of known problems
- Updated Code to match CodeXGlue Repository (has been changed since initial checkout)
- Updated Composes to only use one GPU default
2 changes: 1 addition & 1 deletion docker-compose-minimal.yml
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version: '3.8'

services:
experiment:
codebert_minimal_example:
image: ciselab/codebert-code2text
build:
context: .
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2 changes: 1 addition & 1 deletion docker-compose-pretrained-minimal.yml
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version: '3.8'

services:
experiment:
codebert_prediction_minimal_example:
image: ciselab/codebert-code2text
volumes:
- ./dataset/java/:/dataset:ro
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6 changes: 3 additions & 3 deletions docker-compose-python.yml
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version: '3.8'

services:
python-codebert-training:
codebert_python_training:
image: ciselab/codebert-code2text:1.3
volumes:
- ./dataset/java/:/dataset:ro
- ./compose_output:/experiment/output
- ./dataset/python/:/dataset:ro
- ./python_compose_output:/experiment/output
environment:
epochs: 10
lang: python
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4 changes: 2 additions & 2 deletions docker-compose.yml
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version: '3.8'

services:
experiment:
codebert_java_training:
image: ciselab/codebert-code2text
volumes:
- ./dataset/java/:/dataset:ro
- ./compose_output:/experiment/output
- ./java_compose_output:/experiment/output
environment:
epochs: 10
train_file: /dataset/train.jsonl
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