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# By default, TensorFlow maps nearly all of the GPU memory visible to the process.
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# This is causing issue when other libraries are trying to run tests using a GPU.
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# See: https://www.tensorflow.org/guide/gpu#allowing_gpu_memory_growth
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+ #
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+ # Note about `--hostname localhost` (b/158137436)
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+ # hostname defaults to the container name which fails DNS name
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+ # resolution with --net=none (required to keep tests hermetic). See details in bug.
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docker run --rm -t --read-only --net=none \
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-e HOME=/tmp -e KAGGLE_DATA_PROXY_TOKEN=test-key \
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-e KAGGLE_USER_SECRETS_TOKEN_KEY=test-secrets-key \
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-e KAGGLE_URL_BASE=http://127.0.0.1:8001 \
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-e KAGGLE_DATA_PROXY_URL=http://127.0.0.1:8000 \
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-e KAGGLE_DATA_PROXY_PROJECT=test \
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-e TF_FORCE_GPU_ALLOW_GROWTH=true \
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- # b/158137436: hostname defaults to the container name which fails DNS name
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- # resolution with --net=none (required to keep tests hermetic). See details in bug.
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--hostname localhost \
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--shm-size=2g \
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-v $PWD :/input:ro -v /tmp/python-build/working:/working \
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