update some TF file

TensorFlow/ComputeVision/Classification/README.md

+
+
+TenorFlow 框架 训练 图像分类相关网络的代码,tensorflow 官方基准测试程序，使用的数据集是 imagenet。
+
+# 测试运行
+
+- 测试代码分为两部分，基础性能测试和大规模性能测试。
+
+## 基础 benchmark
+
+- 创建 TensorFlow 运行时环境后，以 resnet50 网络为例，计算其 batch_size=32 num_gpu=1 条件下不同精度下的性能。
+
+### fp32 train
+
+     python3 ./benchmarks-master/scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --data_format=NCHW --batch_size=128 --model=resnet50 --save_model_steps=10020 --optimizer=momentum --variable_update=parameter_server  --print_training_accuracy=true  --eval_during_training_every_n_epochs=1  --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
+
+### fp16 train
+
+    python3  ./benchmarks-master/scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --data_format=NCHW --batch_size=128 --model=resnet50 --save_model_steps=10020 --optimizer=momentum --variable_update=parameter_server  --print_training_accuracy=true  --eval_during_training_every_n_epochs=1  --nodistortions --num_gpus=1 --num_epochs=90 --weight_decay=1e-4 --data_dir=$data_dir_path   --use_fp16=True --data_name=imagenet --train_dir=$save_checkpoint_path
+
+## 大规模测试
+
+### 单卡
+
+    HIP_VISIBLE_DEVICES=0  python3 ./benchmarks-master/scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --data_format=NCHW --batch_size=128 --model=resnet50 --save_model_steps=10020 --optimizer=momentum --variable_update=parameter_server  --print_training_accuracy=true  --eval_during_training_every_n_epochs=1  --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
+
+### 多卡
+
+    mpirun -np ${num_gpu} --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/horovod/horovod]
+

TensorFlow/ComputeVision/Classification/benchmarks-master/.gitignore

+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+*.sw[op]
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*,cover
+.hypothesis/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# IPython Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# dotenv
+.env
+
+# virtualenv
+venv/
+ENV/
+
+# Spyder project settings
+.spyderproject
+
+# Rope project settings
+.ropeproject
+
+# PyCharm
+.idea/
+
+# For mac
+.DS_Store

TensorFlow/ComputeVision/Classification/benchmarks-master/LICENSE

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TensorFlow/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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/ComputeVision/Classification/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