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https://github.com/facebookresearch/pytorch3d.git
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b149bbfb3c
Summary: Script to execute tutorials inside docker with the nightly build. Reviewed By: nikhilaravi Differential Revision: D24503200 fbshipit-source-id: cfa010a7750627d4e87d224a112ff77952feeb55
53 lines
1.8 KiB
Bash
53 lines
1.8 KiB
Bash
#!/usr/bin/bash
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# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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# This script is for running some of the tutorials using the nightly build in
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# an isolated environment. It is designed to be run in docker.
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# If you run this script in this directory with
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# sudo docker run --runtime=nvidia -it --rm -v $PWD/../docs/tutorials:/notebooks -v $PWD:/loc pytorch/conda-cuda bash /loc/run_tutorials.sh | tee log.txt
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# it should execute some tutorials with the nightly build and resave them, and
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# save a log in the current directory.
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# We use nbconvert. runipy would be an alternative but it currently doesn't
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# work well with plotly.
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set -e
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conda init bash
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# shellcheck source=/dev/null
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source ~/.bashrc
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conda create -y -n myenv python=3.8 matplotlib ipython ipywidgets nbconvert
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conda activate myenv
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conda install -y -c conda-forge fvcore
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conda install -y -c pytorch pytorch=1.6.0 cudatoolkit=10.1 torchvision
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conda install -y -c pytorch3d-nightly pytorch3d
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pip install plotly scikit-image
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for notebook in /notebooks/*.ipynb
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do
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name=$(basename "$notebook")
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if [[ "$name" == "dataloaders_ShapeNetCore_R2N2.ipynb" ]]
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then
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#skip as data not easily available
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continue
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fi
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if [[ "$name" == "render_densepose.ipynb" ]]
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then
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#skip as data not easily available
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continue
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fi
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#comment the lines which install torch, torchvision and pytorch3d
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sed -Ei '/(torchvision)|(pytorch3d)/ s/!pip/!#pip/' "$notebook"
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#Don't let tqdm use widgets
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sed -i 's/from tqdm.notebook import tqdm/from tqdm import tqdm/' "$notebook"
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echo
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echo "### ### ###"
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echo "starting $name"
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time jupyter nbconvert --to notebook --inplace --ExecutePreprocessor.kernel_name=python3 --execute "$notebook" || true
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echo "ending $name"
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done
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