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Jing ChenandgVisor bot
57a338f87e
Improve caching, linter compliance, and runtime image sizes. Notable image size reductions: - syscallbench: 160MB drop (~250 MB -> ~90 MB) by converting to a multi-stage build (AS build) to strip gcc and build tools from the runtime image. - absl: 80MB drop (665MB -> 486MB) by combining Bazel installer download, execution, and cleanup into a single RUN layer. - build-grpc : 450MB drop (1.38GB -> 830MB) by removing temporary bazel-*.sh installer scripts from intermediate layers and adding --no-install-recommends. - tensorflow: 60MB (1.29GB -> 1.23GB) drop by clearing /var/lib/apt/lists/* cache. - util: 56MB (137MB -> 81MB) by clearing apt cache lists. PiperOrigin-RevId: 958783211
23 lines
1.3 KiB
Docker
23 lines
1.3 KiB
Docker
FROM tensorflow/tensorflow:1.13.2
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RUN apt-get update \
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&& apt-get install -y --no-install-recommends git ca-certificates \
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&& rm -rf /var/lib/apt/lists/*
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RUN git clone --depth 1 https://github.com/aymericdamien/TensorFlow-Examples.git
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RUN python -m pip install --no-cache-dir -U pip setuptools matplotlib
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# Run the Tensorflow examples; they use the CPU only, but what we want here
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# is the side-effect of pre-downloading the models they will use.
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RUN export PYTHONPATH=$PYTHONPATH:/TensorFlow-Examples/examples; \
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cd /TensorFlow-Examples/examples; \
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examples=' \
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2_BasicModels/kmeans.py \
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2_BasicModels/logistic_regression.py \
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2_BasicModels/nearest_neighbor.py \
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2_BasicModels/random_forest.py \
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3_NeuralNetworks/convolutional_network.py \
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3_NeuralNetworks/multilayer_perceptron.py \
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3_NeuralNetworks/neural_network.py \
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'; \
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for f in $examples; do python "$f"; done
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