Merge branch 'qianyj_tf' into 'main'

update tf code

See merge request dcutoolkit/deeplearing/dlexamples_new!35

TensorFlow/Accuracy_Validation/README.md

+# 简介
+
+该测试用例可用于ResNet50/Vgg16等网络的性能测试及精度验证。 
+
+# 单卡测试 (单精度)
+
+## 运行
+    
+    export HIP_VISIBLE_DEVICES=0  
+    python3 ./benchmarks-master/scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --data_format=NCHW --batch_size=128 --model=resnet50 --optimizer=momentum --variable_update=parameter_server  --print_training_accuracy=true  --nodistortions --num_gpus=1 --num_epochs=90 --weight_decay=1e-4 --data_dir=$data_dir_path   --use_fp16=False --data_name=imagenet --train_dir=$save_checkpoint_path
+
+# 单卡测试 (混合精度)
+
+## 运行
+    export HIP_VISIBLE_DEVICES=0    
+    python3 ./benchmarks-master/scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --data_format=NCHW --batch_size=128 --model=resnet50 --optimizer=momentum --variable_update=parameter_server  --print_training_accuracy=true  --nodistortions --num_gpus=4 --num_epochs=90 --weight_decay=1e-4 --data_dir=$data_dir_path   --use_fp16=True --data_name=imagenet --train_dir=$save_checkpoint_path
+
+# 多卡测试 (单精度)
+
+## 运行
+
+    mpirun -np 4 --hostfile hostfile --bind-to none scripts-run/single_process.sh 
+    
+# 参考资料
+[https://github.com/tensorflow/benchmarks/tree/master/scripts/tf_cnn_benchmarks](https://github.com/tensorflow/benchmarks/tree/master/scripts/tf_cnn_benchmarks)
+

TensorFlow/ComputeVision/Accuracy_Validation/ResNet50_Official/.gitignore → TensorFlow/Accuracy_Validation/benchmarks-master/.gitignore

@@ -2,6 +2,7 @@
 __pycache__/
 *.py[cod]
 *$py.class
+*.sw[op]
 
 # C extensions
 *.so
@@ -15,7 +16,6 @@ dist/
 downloads/
 eggs/
 .eggs/
-lib/
 lib64/
 parts/
 sdist/
@@ -93,5 +93,3 @@ ENV/
 
 # For mac
 .DS_Store
-
-samples/outreach/blogs/segmentation_blogpost/carvana-image-masking-challenge/

TensorFlow/ComputeVision/Accuracy_Validation/ResNet50_Official/LICENSE → TensorFlow/Accuracy_Validation/benchmarks-master/LICENSE

-Copyright 2016 The TensorFlow Authors.  All rights reserved.
-
                                  Apache License
                            Version 2.0, January 2004
                         http://www.apache.org/licenses/
@@ -180,7 +178,7 @@ Copyright 2016 The TensorFlow Authors.  All rights reserved.
    APPENDIX: How to apply the Apache License to your work.
 
       To apply the Apache License to your work, attach the following
-      boilerplate notice, with the fields enclosed by brackets "[]"
+      boilerplate notice, with the fields enclosed by brackets "{}"
       replaced with your own identifying information. (Don't include
       the brackets!)  The text should be enclosed in the appropriate
       comment syntax for the file format. We also recommend that a
@@ -188,7 +186,7 @@ Copyright 2016 The TensorFlow Authors.  All rights reserved.
       same "printed page" as the copyright notice for easier
       identification within third-party archives.
 
-   Copyright 2016, The Authors.
+   Copyright {yyyy} {name of copyright owner}
 
    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_build

+# Ubuntu 18.04 Python3 with CUDA 10 and the following:
+#  - Installs tf-nightly-gpu-2.0-preview
+#  - Installs requirements.txt for tensorflow/models
+#  - Install bazel for building TF from source
+
+FROM nvidia/cuda:10.0-base-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu-2.0-preview"
+ARG extra_pip_specs=""
+ARG local_tensorflow_pip_spec=""
+
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-10-0 \
+        cuda-cublas-dev-10-0 \
+        cuda-cufft-dev-10-0 \
+        cuda-curand-dev-10-0 \
+        cuda-cusolver-dev-10-0 \
+        cuda-cusparse-dev-10-0 \
+        libcudnn7=7.6.2.24-1+cuda10.0  \
+        libcudnn7-dev=7.6.2.24-1+cuda10.0  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl \
+        && \
+  find /usr/local/cuda-10.0/lib64/ -type f -name 'lib*_static.a' -not -name 'libcudart_static.a' -delete && \
+    rm /usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libnvinfer5=5.1.5-1+cuda10.0 \
+    libnvinfer-dev=5.1.5-1+cuda10.0 \
+    && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      build-essential \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python
+# (bulding TF needs py2 even if building for Python3 as of 06-AUG-2019)
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv \
+      python
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client pyyaml google-cloud google-cloud-bigquery google-cloud-datastore mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip3 install -r /tmp/requirements.txt
+
+RUN pip3 freeze
+
+# Install bazel
+ARG BAZEL_VERSION=0.24.1
+RUN mkdir /bazel && \
+    wget -O /bazel/installer.sh "https://github.com/bazelbuild/bazel/releases/download/${BAZEL_VERSION}/bazel-${BAZEL_VERSION}-installer-linux-x86_64.sh" && \
+    wget -O /bazel/LICENSE.txt "https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE" && \
+    chmod +x /bazel/installer.sh && \
+    /bazel/installer.sh && \
+    rm -f /bazel/installer.sh
+
+RUN git clone https://github.com/tensorflow/tensorflow.git /tensorflow_src

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_s4tf_cuda10.0

+# Ubuntu 18.04 Python3 with CUDA 10 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.0)
+#  - Installs requirements.txt for tensorflow/models
+# Additionally also installs:
+#  - Latest S4TF development snapshot for cuda 10.0
+
+FROM nvidia/cuda:10.0-base-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+ARG swift_tf_url=https://storage.googleapis.com/swift-tensorflow-artifacts/nightlies/latest/swift-tensorflow-DEVELOPMENT-cuda10.0-cudnn7-ubuntu18.04.tar.gz
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-10-0 \
+        cuda-cublas-10-0 \
+        cuda-cublas-dev-10-0 \
+        cuda-cufft-10-0 \
+        cuda-curand-10-0 \
+        cuda-cusolver-10-0 \
+        cuda-cusparse-10-0 \
+        libcudnn7=7.6.2.24-1+cuda10.0  \
+        libcudnn7-dev=7.6.2.24-1+cuda10.0  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libnvinfer5=5.1.5-1+cuda10.0 \
+    libnvinfer-dev=5.1.5-1+cuda10.0 \
+    && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client pyyaml google-cloud google-cloud-bigquery mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip freeze
+
+### Install Swift deps.
+ENV DEBIAN_FRONTEND=noninteractive
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        ca-certificates \
+        curl \
+        git \
+        python \
+        python-dev \
+        python-pip \
+        python-setuptools \
+        python-tk \
+        python3 \
+        python3-pip \
+        python3-setuptools \
+        clang \
+        libcurl4-openssl-dev \
+        libicu-dev \
+        libpython-dev \
+        libpython3-dev \
+        libncurses5-dev \
+        libxml2 \
+        libblocksruntime-dev
+
+# Download and extract S4TF
+WORKDIR /swift-tensorflow-toolchain
+RUN if ! curl -fSsL --retry 5 $swift_tf_url -o swift.tar.gz; \
+    then sleep 30 && curl -fSsL --retry 5 $swift_tf_url -o swift.tar.gz; \
+    fi;
+
+RUN mkdir usr \
+    && tar -xzf swift.tar.gz --directory=usr --strip-components=1 \
+    && rm swift.tar.gz
+ENV PATH="/swift-tensorflow-toolchain/usr/bin:${PATH}"
+ENV LD_LIBRARY_PATH="/swift-tensorflow-toolchain/usr/lib/swift/linux/:${LD_LIBRARY_PATH}"

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_s4tf_cuda10.1

+# Ubuntu 18.04 Python3 with CUDA 10.1 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.1)
+#  - Installs requirements.txt for tensorflow/models
+#  - TF 2.0 tested with cuda 10.0, but we need to test tf 2.1 with cuda 10.1.
+# Additionally also installs
+#  - Latest S4TF development snapshot for cuda 10.1
+
+FROM nvidia/cuda:10.1-base-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+ARG swift_tf_url=https://storage.googleapis.com/swift-tensorflow-artifacts/nightlies/latest/swift-tensorflow-DEVELOPMENT-cuda10.1-cudnn7-stock-ubuntu18.04.tar.gz
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-10-1 \
+        cuda-cufft-10-1 \
+        cuda-curand-10-1 \
+        cuda-cusolver-10-1 \
+        cuda-cusparse-10-1 \
+        libcudnn7=7.6.4.38-1+cuda10.1  \
+        libcudnn7-dev=7.6.4.38-1+cuda10.1  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libnvinfer5=5.1.5-1+cuda10.1 \
+    libnvinfer-dev=5.1.5-1+cuda10.1 \
+    libnvinfer6=6.0.1-1+cuda10.1 \
+    && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client pyyaml google-cloud google-cloud-bigquery google-cloud-datastore mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip freeze
+
+### Install Swift deps.
+ENV DEBIAN_FRONTEND=noninteractive
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        ca-certificates \
+        curl \
+        git \
+        python \
+        python-dev \
+        python-pip \
+        python-setuptools \
+        python-tk \
+        python3 \
+        python3-pip \
+        python3-setuptools \
+        clang \
+        libcurl4-openssl-dev \
+        libicu-dev \
+        libpython-dev \
+        libpython3-dev \
+        libncurses5-dev \
+        libxml2 \
+        libblocksruntime-dev
+
+# Download and extract S4TF
+WORKDIR /swift-tensorflow-toolchain
+RUN if ! curl -fSsL --retry 5 $swift_tf_url -o swift.tar.gz; \
+    then sleep 30 && curl -fSsL --retry 5 $swift_tf_url -o swift.tar.gz; \
+    fi;
+
+RUN mkdir usr \
+    && tar -xzf swift.tar.gz --directory=usr --strip-components=1 \
+    && rm swift.tar.gz
+ENV PATH="/swift-tensorflow-toolchain/usr/bin:${PATH}"
+ENV LD_LIBRARY_PATH="/swift-tensorflow-toolchain/usr/lib/swift/linux/:${LD_LIBRARY_PATH}"

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_s4tf_cuda11.0

+# Ubuntu 18.04 Python3 with CUDA 11.0 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.4)
+#  - Installs requirements.txt for tensorflow/models
+# Additionally also installs
+#  - Latest S4TF development snapshot for cuda 11.0
+
+FROM nvidia/cuda:11.0-base-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+ARG swift_tf_url=https://storage.googleapis.com/swift-tensorflow-artifacts/nightlies/latest/swift-tensorflow-DEVELOPMENT-cuda11.0-cudnn8-stock-ubuntu18.04.tar.gz
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn8-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-tools-11-0 \
+        cuda-toolkit-11-0 \
+        libcudnn8=8.0.4.30-1+cuda11.0  \
+        libcudnn8-dev=8.0.4.30-1+cuda11.0  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libnvinfer7=7.2.0-1+cuda11.0 \
+    libnvinfer-dev=7.2.0-1+cuda11.0 \
+    && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client pyyaml google-cloud google-cloud-bigquery google-cloud-datastore mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip freeze
+
+### Install Swift deps.
+ENV DEBIAN_FRONTEND=noninteractive
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        ca-certificates \
+        curl \
+        git \
+        python \
+        python-dev \
+        python-pip \
+        python-setuptools \
+        python-tk \
+        python3 \
+        python3-pip \
+        python3-setuptools \
+        clang \
+        libcurl4-openssl-dev \
+        libicu-dev \
+        libpython-dev \
+        libpython3-dev \
+        libncurses5-dev \
+        libxml2 \
+        libblocksruntime-dev
+
+# Download and extract S4TF
+WORKDIR /swift-tensorflow-toolchain
+RUN if ! curl -fSsL --retry 5 $swift_tf_url -o swift.tar.gz; \
+    then sleep 30 && curl -fSsL --retry 5 $swift_tf_url -o swift.tar.gz; \
+    fi;
+
+RUN mkdir usr \
+    && tar -xzf swift.tar.gz --directory=usr --strip-components=1 \
+    && rm swift.tar.gz
+ENV PATH="/swift-tensorflow-toolchain/usr/bin:${PATH}"
+ENV LD_LIBRARY_PATH="/swift-tensorflow-toolchain/usr/lib/swift/linux/:${LD_LIBRARY_PATH}"

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_testing_apiclient

+# Ubuntu 18.04 Python3 with CUDA 10.1 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.1)
+#  - Installs requirements.txt for tensorflow/models
+#  - TF 2.0 tested with cuda 10.0, but we need to test tf 2.1 with cuda 10.1.
+
+FROM nvidia/cuda:10.1-base-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-10-1 \
+        cuda-cufft-10-1 \
+        cuda-curand-10-1 \
+        cuda-cusolver-10-1 \
+        cuda-cusparse-10-1 \
+        libcudnn7=7.6.4.38-1+cuda10.1  \
+        libcudnn7-dev=7.6.4.38-1+cuda10.1  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libnvinfer5=5.1.5-1+cuda10.1 \
+    libnvinfer-dev=5.1.5-1+cuda10.1 \
+    libnvinfer6=6.0.1-1+cuda10.1 \
+    && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client==1.8.0 pyyaml google-cloud google-cloud-bigquery mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_cuda_11

+# Ubuntu 18.04 Python3 with CUDA 11 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.3)
+#  - Installs requirements.txt for tensorflow/models
+
+FROM nvidia/cuda:11.2.1-cudnn8-devel-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+ENV PIP_CMD="python3.9 -m pip"
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+# Needed to disable prompts during installation.
+ENV DEBIAN_FRONTEND noninteractive
+
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+# Python 3.9 related deps in this ppa.
+RUN add-apt-repository ppa:deadsnakes/ppa
+
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3.9 \
+      python3-pip \
+      python3.9-dev \
+      python3-setuptools \
+      python3.9-venv \
+      python3.9-distutils \
+      python3.9-lib2to3
+      
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN ${PIP_CMD} install --upgrade pip
+RUN ${PIP_CMD} install --upgrade distlib
+# setuptools upgraded to fix install requirements from model garden.
+RUN ${PIP_CMD} install --upgrade setuptools
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.2/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+RUN ${PIP_CMD} install --upgrade pyyaml
+RUN ${PIP_CMD} install --upgrade google-api-python-client==1.8.0
+RUN ${PIP_CMD} install --upgrade google-cloud google-cloud-bigquery google-cloud-datastore mock
+
+
+RUN ${PIP_CMD} install wheel
+RUN ${PIP_CMD} install absl-py
+RUN ${PIP_CMD} install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+
+RUN ${PIP_CMD} install tfds-nightly
+RUN ${PIP_CMD} install -U scikit-learn
+
+# Install dependnecies needed for tf.distribute test utils
+RUN ${PIP_CMD} install dill tblib portpicker
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN ${PIP_CMD} install -r /tmp/requirements.txt
+
+RUN ${PIP_CMD} install tf-estimator-nightly
+RUN ${PIP_CMD} install tensorflow-text-nightly
+
+# RUN nvidia-smi
+
+RUN nvcc --version
+
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_cuda_11_0

+# Ubuntu 18.04 Python3 with CUDA 11 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.3)
+#  - Installs requirements.txt for tensorflow/models
+
+FROM nvidia/cuda:11.0-cudnn8-devel-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-tools-11-0 \
+        cuda-toolkit-11-0 \
+        libcudnn8=8.0.4.30-1+cuda11.0  \
+        libcudnn8-dev=8.0.4.30-1+cuda11.0  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.0/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client==1.8.0 pyyaml google-cloud google-cloud-bigquery google-cloud-datastore mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+# Install dependnecies needed for tf.distribute test utils
+RUN pip install dill tblib portpicker
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip install tf-estimator-nightly
+RUN pip install tensorflow-text-nightly
+
+# RUN nvidia-smi
+
+RUN nvcc --version
+
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_cuda_11_py36

+# Ubuntu 18.04 Python3 with CUDA 11 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.3)
+#  - Installs requirements.txt for tensorflow/models
+
+FROM nvidia/cuda:11.2.1-cudnn8-devel-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.2/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client==1.8.0 pyyaml google-cloud google-cloud-bigquery google-cloud-datastore mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+# Install dependnecies needed for tf.distribute test utils
+RUN pip install dill tblib portpicker
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip install tf-estimator-nightly
+RUN pip install tensorflow-text-nightly
+RUN pip install psutil
+
+# RUN nvidia-smi
+
+RUN nvcc --version
+
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_cuda_11_rollback

+# Ubuntu 18.04 Python3 with CUDA 11 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.3)
+#  - Installs requirements.txt for tensorflow/models
+
+FROM nvidia/cuda:11.2.1-cudnn8-devel-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+ENV PIP_CMD="python3.9 -m pip"
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+# Needed to disable prompts during installation.
+ENV DEBIAN_FRONTEND noninteractive
+
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+# Python 3.9 related deps in this ppa.
+RUN add-apt-repository ppa:deadsnakes/ppa
+
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3.9 \
+      python3-pip \
+      python3.9-dev \
+      python3-setuptools \
+      python3.9-venv \
+      python3.9-distutils \
+      python3.9-lib2to3
+      
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN ${PIP_CMD} install --upgrade pip
+RUN ${PIP_CMD} install --upgrade distlib
+# setuptools upgraded to fix install requirements from model garden.
+RUN ${PIP_CMD} install --upgrade setuptools
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.2/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+RUN ${PIP_CMD} install --upgrade pyyaml
+RUN ${PIP_CMD} install --upgrade google-api-python-client==1.8.0
+RUN ${PIP_CMD} install --upgrade google-cloud google-cloud-bigquery google-cloud-datastore mock
+
+
+RUN ${PIP_CMD} install wheel
+RUN ${PIP_CMD} install absl-py
+RUN ${PIP_CMD} install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+
+RUN ${PIP_CMD} install tfds-nightly
+RUN ${PIP_CMD} install -U scikit-learn
+
+# Install dependnecies needed for tf.distribute test utils
+RUN ${PIP_CMD} install dill tblib portpicker
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN ${PIP_CMD} install -r /tmp/requirements.txt
+
+RUN ${PIP_CMD} install tf-estimator-nightly
+RUN ${PIP_CMD} install tensorflow-text-nightly
+RUN ${PIP_CMD} install keras-nightly==2.7.0.dev2021082607
+
+# RUN nvidia-smi
+
+RUN nvcc --version
+
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_cuda_11_rollback_2

+# Ubuntu 18.04 Python3 with CUDA 11 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.3)
+#  - Installs requirements.txt for tensorflow/models
+
+FROM nvidia/cuda:11.2.1-cudnn8-devel-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+ENV PIP_CMD="python3.9 -m pip"
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+# Needed to disable prompts during installation.
+ENV DEBIAN_FRONTEND noninteractive
+
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+# Python 3.9 related deps in this ppa.
+RUN add-apt-repository ppa:deadsnakes/ppa
+
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3.9 \
+      python3-pip \
+      python3.9-dev \
+      python3-setuptools \
+      python3.9-venv \
+      python3.9-distutils \
+      python3.9-lib2to3
+      
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN ${PIP_CMD} install --upgrade pip
+RUN ${PIP_CMD} install --upgrade distlib
+# setuptools upgraded to fix install requirements from model garden.
+RUN ${PIP_CMD} install --upgrade setuptools
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.2/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+RUN ${PIP_CMD} install --upgrade pyyaml
+RUN ${PIP_CMD} install --upgrade google-api-python-client==1.8.0
+RUN ${PIP_CMD} install --upgrade google-cloud google-cloud-bigquery google-cloud-datastore mock
+
+
+RUN ${PIP_CMD} install wheel
+RUN ${PIP_CMD} install absl-py
+RUN ${PIP_CMD} install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+
+RUN ${PIP_CMD} install tfds-nightly
+RUN ${PIP_CMD} install -U scikit-learn
+
+# Install dependnecies needed for tf.distribute test utils
+RUN ${PIP_CMD} install dill tblib portpicker
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN ${PIP_CMD} install -r /tmp/requirements.txt
+
+RUN ${PIP_CMD} install tf-estimator-nightly
+RUN ${PIP_CMD} install tensorflow-text-nightly
+RUN ${PIP_CMD} install keras-nightly==2.7.0.dev2021070900
+
+# RUN nvidia-smi
+
+RUN nvcc --version
+
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_cuda_testing

+# Ubuntu 18.04 Python3 with CUDA 11 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.3)
+#  - Installs requirements.txt for tensorflow/models
+
+FROM nvidia/cuda:11.0-cudnn8-devel-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-tools-11-0 \
+        cuda-toolkit-11-0 \
+        libcudnn8=8.0.4.30-1+cuda11.0  \
+        libcudnn8-dev=8.0.4.30-1+cuda11.0  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda-11.0/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client==1.8.0 pyyaml google-cloud google-cloud-bigquery google-cloud-datastore mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+# Install dependnecies needed for tf.distribute test utils
+RUN pip install dill tblib portpicker
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip install tf-estimator-nightly
+RUN pip install tensorflow-text-nightly
+
+# RUN nvidia-smi
+
+RUN nvcc --version
+
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_custom_pip

+# Ubuntu 18.04 Python3.6 with CUDA 10 and the following:
+#  - Installs custom TensorFlow pip package
+#  - Installs requirements.txt for tensorflow/models
+
+# NOTE: Branched from Dockerfile_ubuntu_1804_tf_v1 with changes relevant to
+# tensorflow_pip_spec. When updating please keep the difference minimal.
+
+FROM nvidia/cuda:10.0-base-ubuntu18.04 as base
+
+# Location of custom TF pip package, must be relative to docker context.
+# Note that the version tag in the name of wheel file is meaningless.
+ARG tensorflow_pip_spec="resources/tensorflow-0.0.1-cp36-cp36m-linux_x86_64.whl"
+ARG extra_pip_specs=""
+ARG local_tensorflow_pip_spec=""
+
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+COPY ${tensorflow_pip_spec} /tensorflow-0.0.1-cp36-cp36m-linux_x86_64.whl
+
+# Pick up some TF dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-10-0 \
+        cuda-cublas-10-0 \
+        cuda-cufft-10-0 \
+        cuda-curand-10-0 \
+        cuda-cusolver-10-0 \
+        cuda-cusparse-10-0 \
+        libcudnn7=7.4.1.5-1+cuda10.0 \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+RUN apt-get update && \
+        apt-get install nvinfer-runtime-trt-repo-ubuntu1804-5.0.2-ga-cuda10.0 \
+        && apt-get update \
+        && apt-get install -y --no-install-recommends libnvinfer5=5.0.2-1+cuda10.0 \
+        && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      build-essential \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+
+# Setup Python3 environment
+RUN pip3 install --upgrade pip==9.0.1
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip3 install wheel
+RUN pip3 install --upgrade setuptools google-api-python-client pyyaml google-cloud google-cloud-bigquery
+RUN pip3 install absl-py
+RUN pip3 install --upgrade --force-reinstall /tensorflow-0.0.1-cp36-cp36m-linux_x86_64.whl ${extra_pip_specs}
+RUN pip3 install tfds-nightly
+RUN pip3 install -U scikit-learn
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip3 install -r /tmp/requirements.txt
+
+RUN pip3 freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_v1

+# Ubuntu 18.04 Python3 with CUDA 10 and the following:
+#  - Installs tf-nightly-gpu
+#  - Installs requirements.txt for tensorflow/models
+#
+# This docker is not needed and is the same as the tf_v2 docker. The
+# User can pass in the desired `ARG tensorflow_pip_spec`  Remove
+# one TF 1.0 testing is done or KOKORO jobs are updated to use the
+# tensorfow_pip_spec rather than docker path to control TF version.
+
+FROM nvidia/cuda:10.0-base-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG extra_pip_specs=""
+ARG local_tensorflow_pip_spec=""
+
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-10-0 \
+        cuda-cublas-10-0 \
+        cuda-cublas-dev-10-0 \
+        cuda-cufft-10-0 \
+        cuda-curand-10-0 \
+        cuda-cusolver-10-0 \
+        cuda-cusparse-10-0 \
+        libcudnn7=7.6.0.64-1+cuda10.0  \
+        libcudnn7-dev=7.6.0.64-1+cuda10.0  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libnvinfer5=5.1.5-1+cuda10.0 \
+    libnvinfer-dev=5.1.5-1+cuda10.0 \
+    && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client pyyaml google-cloud google-cloud-bigquery mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_v2

+# Ubuntu 18.04 Python3 with CUDA 10 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.0)
+#  - Installs requirements.txt for tensorflow/models
+
+FROM nvidia/cuda:10.0-base-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-10-0 \
+        cuda-cublas-10-0 \
+        cuda-cublas-dev-10-0 \
+        cuda-cufft-10-0 \
+        cuda-curand-10-0 \
+        cuda-cusolver-10-0 \
+        cuda-cusparse-10-0 \
+        libcudnn7=7.6.2.24-1+cuda10.0  \
+        libcudnn7-dev=7.6.2.24-1+cuda10.0  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libnvinfer5=5.1.5-1+cuda10.0 \
+    libnvinfer-dev=5.1.5-1+cuda10.0 \
+    && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client pyyaml google-cloud google-cloud-bigquery mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tf_v2_1

+# Ubuntu 18.04 Python3 with CUDA 10.1 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.1)
+#  - Installs requirements.txt for tensorflow/models
+#  - TF 2.0 tested with cuda 10.0, but we need to test tf 2.1 with cuda 10.1.
+
+FROM nvidia/cuda:10.1-base-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+# In the future, add the following lines in a shell script running on the
+# benchmark vm to get the available dependent versions when updating cuda
+# version (e.g to 10.2 or something later):
+# sudo apt-cache search cuda-command-line-tool
+# sudo apt-cache search cuda-cublas
+# sudo apt-cache search cuda-cufft
+# sudo apt-cache search cuda-curand
+# sudo apt-cache search cuda-cusolver
+# sudo apt-cache search cuda-cusparse
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-10-1 \
+        cuda-cufft-10-1 \
+        cuda-curand-10-1 \
+        cuda-cusolver-10-1 \
+        cuda-cusparse-10-1 \
+        libcudnn7=7.6.4.38-1+cuda10.1  \
+        libcudnn7-dev=7.6.4.38-1+cuda10.1  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libnvinfer5=5.1.5-1+cuda10.1 \
+    libnvinfer-dev=5.1.5-1+cuda10.1 \
+    libnvinfer6=6.0.1-1+cuda10.1 \
+    && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client==1.8.0 pyyaml google-cloud google-cloud-bigquery google-cloud-datastore mock
+RUN pip install absl-py
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec} ${extra_pip_specs}
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+# Install dependnecies needed for tf.distribute test utils
+RUN pip install dill tblib portpicker
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+RUN pip freeze

TensorFlow/Accuracy_Validation/benchmarks-master/perfzero/docker/Dockerfile_ubuntu_1804_tfx

+# Ubuntu 18.04 Python3 with CUDA 10 and the following:
+#  - Installs tf-nightly-gpu (this is TF 2.0)
+#  - Installs requirements.txt for tensorflow/models
+#
+# NOTE: Branched from Dockerfile_ubuntu_1804_tf_v2 with changes for
+# TFX benchmarks.
+
+FROM nvidia/cuda:10.0-base-ubuntu18.04 as base
+ARG tensorflow_pip_spec="tf-nightly-gpu"
+ARG local_tensorflow_pip_spec=""
+ARG extra_pip_specs=""
+
+# Specifies the default package version to use if no corresponding commit_id
+# override is specified.
+# If "head", uses the GitHub HEAD version.
+# If "release", uses the latest released version from PyPI, REGARDLESS of
+# package-compatibility requirements (e.g. even if tfx requires
+# tensorflow-model-analysis<0.22, if tensorflow-model-analysis==0.22.0 is
+# the latest released version on PyPI, we will install that).
+# Packages include: tfx, tensorflow-transform, tensorflow-model-analysis,
+# tensorflow-data-validation, tensorflow-metadata, tfx-bsl
+ARG default_package_version="head"
+
+# Specifies the package version to use for the corresponding packages.
+# If empty, uses the default specified by default_package_version.
+# If "head", uses the GitHub HEAD version.
+# If "release", uses the latest released version from PyPI, REGARDLESS of
+# package-compatibility requirements.
+# If "github_commit:<commit id>", uses the given commit ID from GitHub.
+# If "github_tag:<tag>" uses the given tag from GitHub.
+# If "pypi:<version string>", uses the given package version from PyPI.
+ARG tfx_package_version=""
+ARG tensorflow_transform_package_version=""
+ARG tensorflow_model_analysis_package_version=""
+ARG tensorflow_data_validation_package_version=""
+ARG tensorflow_metadata_package_version=""
+ARG tfx_bsl_version=""
+
+# setup.py passes the base path of local .whl file is chosen for the docker image.
+# Otherwise passes an empty existing file from the context.
+COPY ${local_tensorflow_pip_spec} /${local_tensorflow_pip_spec}
+
+# Pick up some TF dependencies
+# cublas-dev and libcudnn7-dev only needed because of libnvinfer-dev which may not
+# really be needed.
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-10-0 \
+        cuda-cublas-10-0 \
+        cuda-cublas-dev-10-0 \
+        cuda-cufft-10-0 \
+        cuda-curand-10-0 \
+        cuda-cusolver-10-0 \
+        cuda-cusparse-10-0 \
+        libcudnn7=7.6.2.24-1+cuda10.0  \
+        libcudnn7-dev=7.6.2.24-1+cuda10.0  \
+        libfreetype6-dev \
+        libhdf5-serial-dev \
+        libzmq3-dev \
+        libpng-dev \
+        pkg-config \
+        software-properties-common \
+        unzip \
+        lsb-core \
+        curl
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends libnvinfer5=5.1.5-1+cuda10.0 \
+    libnvinfer-dev=5.1.5-1+cuda10.0 \
+    && apt-get clean
+
+# For CUDA profiling, TensorFlow requires CUPTI.
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+
+# See http://bugs.python.org/issue19846
+ENV LANG C.UTF-8
+
+# Add google-cloud-sdk to the source list
+RUN echo "deb http://packages.cloud.google.com/apt cloud-sdk-$(lsb_release -c -s) main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
+RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
+
+# Install extras needed by most models
+RUN apt-get update && apt-get install -y --no-install-recommends \
+      git \
+      ca-certificates \
+      wget \
+      htop \
+      zip \
+      google-cloud-sdk
+
+# Install / update Python and Python3
+RUN apt-get install -y --no-install-recommends \
+      python3 \
+      python3-dev \
+      python3-pip \
+      python3-setuptools \
+      python3-venv
+
+
+# Upgrade pip, need to use pip3 and then pip after this or an error
+# is thrown for no main found.
+RUN pip3 install --upgrade pip
+# setuptools upgraded to fix install requirements from model garden.
+RUN pip install wheel
+RUN pip install --upgrade setuptools google-api-python-client pyyaml google-cloud google-cloud-bigquery google-cloud-datastore mock
+RUN pip install absl-py
+RUN if [ ! -z "${extra_pip_specs}" ]; then pip install --upgrade --force-reinstall ${extra_pip_specs}; fi
+RUN pip install tfds-nightly
+RUN pip install -U scikit-learn
+
+RUN curl https://raw.githubusercontent.com/tensorflow/models/master/official/requirements.txt > /tmp/requirements.txt
+RUN pip install -r /tmp/requirements.txt
+
+# Install yolk3k, for getting package versions from PyPI (so we can pull
+# TFX from GitHub even when we need to install from the released version)
+RUN pip install yolk3k
+
+# Install protoc
+RUN PROTOC_ZIP=protoc-3.7.1-linux-x86_64.zip; \
+    curl -OL https://github.com/protocolbuffers/protobuf/releases/download/v3.7.1/$PROTOC_ZIP; \
+    unzip -o $PROTOC_ZIP -d /usr/local bin/protoc; \
+    unzip -o $PROTOC_ZIP -d /usr/local 'include/*'; \
+    rm -f $PROTOC_ZIP;
+
+# Install Bazel
+RUN curl https://bazel.build/bazel-release.pub.gpg | apt-key add -
+RUN echo "deb [arch=amd64] https://storage.googleapis.com/bazel-apt stable jdk1.8" | tee /etc/apt/sources.list.d/bazel.list
+RUN apt update
+RUN apt install bazel
+# Create symlink to "python3" binary under the name "python" so Bazel doesn't complain about "python" not being found
+RUN ln -s $(which python3) /usr/bin/python
+
+SHELL ["/bin/bash", "-c"]
+RUN \
+  function install_package { \
+    # e.g. "head" or "release" \
+    default_version="$1"; \
+    # e.g "tensorflow-model-analysis" \
+    package_name="$2"; \
+    # e.g "model-analysis" \
+    package_repo_name="$3"; \
+    # How this package should be installed if pulled from GitHub. \
+    # "none" for no extra installation steps required \
+    # "bdist_wheel" for python setup.py bdist_wheel \
+    package_install_type=$4; \
+    # e.g. "head" or "release" or "pypi:0.21.4" or "github:[commit hash]" \
+    package_version="$5"; \
+    \
+    # e.g. "tensorflow_model_analysis" \
+    package_name_underscores=${package_name//-/_}; \
+    if [ "$package_version" == "" ]; then \
+      package_version="$default_version"; \
+    fi; \
+    \
+    commit_id=""; \
+    pypi_version=""; \
+    if [ "$package_version" == "head" ]; then \
+      commit_id=$(git ls-remote https://github.com/tensorflow/${package_repo_name} refs/heads/master | cut -f1); \
+      echo ${package_name}: latest commit from GitHub: ${commit_id}; \
+    elif [ "$package_version" == "release" ]; then \
+      pypi_version=$(yolk -V $package_name | head -n 1 | cut -d' ' -f 2-); \
+      echo ${package_name}: latest version from PyPI: ${pypi_version}; \
+    elif [ "${package_version:0:5}" == "pypi:" ]; then \
+      pypi_version="${package_version:5}"; \
+      echo ${package_name}: using specified PyPI version: ${pypi_version}; \
+    elif [ "${package_version:0:7}" == "github:" ]; then \
+      commit_id="${package_version:7}"; \
+      echo ${package_name}: using specified GitHub commit: ${commit_id}; \
+    else \
+      echo Unknown package version for ${package_name}: ${package_version}; \
+      exit 1; \
+    fi; \
+    \
+    if [ "$commit_id" != "" ]; then \
+      if [ "$package_install_type" == "none" ]; then \
+        # Package doesn't need extra installation steps - install directly from GitHub. \
+        pip install -e git+https://github.com/tensorflow/${package_repo_name}.git@${commit_id}#egg=${package_name_underscores}; \
+        install_commands+=("pip install --force --no-deps -e git+https://github.com/tensorflow/${package_repo_name}.git@${commit_id}#egg=${package_name_underscores}"); \
+        echo Installed ${package_name} from GitHub commit ${commit_id}; \
+      elif [ "$package_install_type" == "bdist_wheel" ]; then \
+        # Package needs extra installation steps. Clone from GitHub, then build and install. \
+        git clone https://github.com/tensorflow/${package_repo_name}.git; \
+        pushd ${package_repo_name}; \
+        git checkout ${commit_id}; \
+        if [ "$package_name" == "tfx" ]; then \
+          echo Building TFX pip package from source; \
+          sed -i 's@packages=packages,@packages=packages, package_data={package_name: ["benchmarks/datasets/chicago_taxi/data/taxi_1M.tfrecords.gz"]},@' setup.py; \
+          package_build/initialize.sh; \
+          python package_build/ml-pipelines-sdk/setup.py bdist_wheel; \
+          python package_build/tfx/setup.py bdist_wheel; \
+        else \
+          echo Using python setup.py bdist_wheel to build package; \
+          python setup.py bdist_wheel; \
+        fi; \
+        pip install dist/*.whl; \
+        install_commands+=("pip install --force --no-deps ${PWD}/dist/*.whl"); \
+        popd; \
+        echo Built and installed ${package_name} from GitHub commit ${commit_id}; \	
+      fi; \
+      # Write GIT_COMMIT_ID attribute to the installed package. \
+      package_path=$(python3 -c "import ${package_name_underscores}; print(list(${package_name_underscores}.__path__)[0])"); \
+      echo "GIT_COMMIT_ID='${commit_id}'" >> ${package_path}/__init__.py; \
+      install_commands+=("echo \"GIT_COMMIT_ID='${commit_id}'\" >> ${package_path}/__init__.py;"); \
+    elif [ "$pypi_version" != "" ]; then \
+      if [ "$package_name" == "tfx" ]; then \
+        # Special handling for TFX - we want to install from GitHub, and get \
+        # the data files as well (they are not included in the pip package). \
+        # Install from the corresponding tag in GitHub. \
+        echo Special handling for tfx: will install tfx from GitHub tag for version ${pypi_version}; \
+        git clone --depth 1 --branch v${pypi_version} https://github.com/tensorflow/tfx.git; \
+        pushd tfx; \
+        echo Building TFX pip package from source; \
+        sed -i 's@packages=packages,@packages=packages, package_data={package_name: ["benchmarks/datasets/chicago_taxi/data/taxi_1M.tfrecords.gz"]},@' setup.py; \
+        package_build/initialize.sh; \
+        python package_build/ml-pipelines-sdk/setup.py bdist_wheel; \
+        python package_build/tfx/setup.py bdist_wheel; \
+        pip install dist/*.whl; \
+        install_commands+=("pip install --force --no-deps ${PWD}/dist/*.whl"); \
+        popd; \
+        echo Installed tfx from GitHub tag for version ${pypi_version}; \
+      else \
+        pip install ${package_name}==${pypi_version}; \
+        install_commands+=("pip install --force --no-deps ${package_name}==${pypi_version}"); \
+        echo Installed ${package_name} from PyPI version ${pypi_version}; \
+      fi; \
+    else \
+      echo Neither commit_id nor pypi_version was set for ${package_name}; \
+      exit 1; \
+    fi; \
+  }; \
+  \
+  # Array of commands to run post-installation. This is for forcing \
+  # installation of packages without regard to the requirements of other \
+  # packages. \
+  # The first round of installations installs the packages and their \
+  # requirements. This may result in some packages being re-installed at \
+  # versions other than the requested versions due to requirements from \
+  # other packages. \
+  # The second round of installations via install_commands \
+  # forces installations of the packages at the desired versions, ignoring \
+  # any dependencies of these packages or other packages. Note that if there \
+  # are incompatible package dependencies (e.g. tfx depends on \
+  # apache-beam==2.21 and tensorflow-transform depends on apache-beam==2.22 \
+  # then either could be installed depending on the installation order). \
+  install_commands=(); \
+  install_package "${default_package_version}" "tfx" "tfx" "bdist_wheel" "${tfx_package_version}"; \
+  install_package "${default_package_version}" "tensorflow-transform" "transform" "none" "${tensorflow_transform_package_version}"; \
+  install_package "${default_package_version}" "tensorflow-model-analysis" "model-analysis" "none" "${tensorflow_model_analysis_package_version}"; \
+  install_package "${default_package_version}" "tensorflow-data-validation" "data-validation" "bdist_wheel" "${tensorflow_data_validation_package_version}"; \
+  install_package "${default_package_version}" "tensorflow-metadata" "metadata" "bdist_wheel" "${tensorflow_metadata_package_version}"; \
+  install_package "${default_package_version}" "tfx-bsl" "tfx-bsl" "bdist_wheel" "${tfx_bsl_package_version}"; \
+  for cmd in "${install_commands[@]}"; do \
+    echo Running "${cmd}"; \
+    eval $cmd; \
+  done;
+
+# Uninstall the TensorFlow version that TFX / the TFX components installed, and
+# force install the version requested.
+RUN pip uninstall -y tensorflow
+RUN pip install --upgrade --force-reinstall ${tensorflow_pip_spec}
+
+RUN pip freeze