@@ -16,29 +16,34 @@ rm -rf src
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pip install -r $DIR /../requirements.txt
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export PATH=/opt/conda/bin:$PATH
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- conda install -y sphinx==1.8.2 pandas
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+ pip install sphinx==1.8.2 pandas
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+
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+ # install awscli
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+ # pip uninstall awscli
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+ # pip install awscli==1.16.35
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+
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# PyTorch Theme
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rm -rf src
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pip install -e git+git://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
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# pillow >= 4.2 will throw error when trying to write mode RGBA as JPEG,
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# this is a workaround to the issue.
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- pip install sphinx-gallery tqdm matplotlib ipython pillow==4.1.1
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+ pip install sphinx-gallery==0.3.1 tqdm matplotlib ipython pillow==4.1.1
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# Install torchaudio from source
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- git clone https://github.com/pytorch/audio --quiet
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- pushd audio
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- python setup.py install
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- popd
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+ # git clone https://github.com/pytorch/audio --quiet
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+ # pushd audio
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+ # python setup.py install
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+ # popd
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aws configure set default.s3.multipart_threshold 5120MB
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# Decide whether to parallelize tutorial builds, based on $JOB_BASE_NAME
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export NUM_WORKERS=20
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if [[ " ${JOB_BASE_NAME} " == * worker_* ]]; then
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# Step 1: Remove runnable code from tutorials that are not supposed to be run
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- python $DIR /remove_runnable_code.py beginner_source/aws_distributed_training_tutorial.py beginner_source/aws_distributed_training_tutorial.py
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+ python $DIR /remove_runnable_code.py beginner_source/aws_distributed_training_tutorial.py beginner_source/aws_distributed_training_tutorial.py || true
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# TODO: Fix bugs in these tutorials to make them runnable again
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- python $DIR /remove_runnable_code.py beginner_source/audio_classifier_tutorial.py beginner_source/audio_classifier_tutorial.py
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+ python $DIR /remove_runnable_code.py beginner_source/audio_classifier_tutorial.py beginner_source/audio_classifier_tutorial.py || true
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# Step 2: Keep certain tutorials based on file count, and remove runnable code in all other tutorials
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# IMPORTANT NOTE: We assume that each tutorial has a UNIQUE filename.
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fi
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rm -rf vision
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- rm -rf audio
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+ # rm -rf audio
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