Add TensorFlow 1.7 dockerfiles

docker/1.7.0/base/Dockerfile.cpu

@@ -0,0 +1,51 @@
+FROM ubuntu:16.04
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        curl \
+        git \
+        libcurl3-dev \
+        libfreetype6-dev \
+        libpng12-dev \
+        libzmq3-dev \
+        pkg-config \
+        python-dev \
+        rsync \
+        software-properties-common \
+        unzip \
+        zip \
+        zlib1g-dev \
+        openjdk-8-jdk \
+        openjdk-8-jre-headless \
+        wget \
+        vim \
+        iputils-ping \
+        nginx \
+        && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py && \
+    python get-pip.py && \
+    rm get-pip.py
+
+RUN pip --no-cache-dir install \
+        numpy \
+        scipy \
+        sklearn \
+        pandas \
+        h5py
+
+WORKDIR /root
+
+ENV TF_SERVING_VERSION=1.7.0
+
+RUN pip install numpy boto3 six awscli flask==0.11 Jinja2==2.9 tensorflow-serving-api==$TF_SERVING_VERSION gevent gunicorn
+
+RUN wget "http://storage.googleapis.com/tensorflow-serving-apt/pool/tensorflow-model-server/t/tensorflow-model-server/tensorflow-model-server_${TF_SERVING_VERSION}_all.deb" && \
+    dpkg -i tensorflow-model-server_${TF_SERVING_VERSION}_all.deb
+
+# Update libstdc++6, as required by tensorflow-serving >= 1.6: https://github.com/tensorflow/serving/issues/819
+RUN add-apt-repository ppa:ubuntu-toolchain-r/test -y && \
+    apt-get update && \
+    apt-get install -y libstdc++6

docker/1.7.0/base/Dockerfile.gpu

@@ -0,0 +1,117 @@
+FROM nvidia/cuda:9.0-base-ubuntu16.04
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        cuda-command-line-tools-9-0 \
+        cuda-cublas-dev-9-0 \
+        cuda-cudart-dev-9-0 \
+        cuda-cufft-dev-9-0 \
+        cuda-curand-dev-9-0 \
+        cuda-cusolver-dev-9-0 \
+        cuda-cusparse-dev-9-0 \
+        curl \
+        git \
+        libcudnn7=7.0.5.15-1+cuda9.0 \
+        libcudnn7-dev=7.0.5.15-1+cuda9.0 \
+        libcurl3-dev \
+        libfreetype6-dev \
+        libpng12-dev \
+        libzmq3-dev \
+        pkg-config \
+        python-dev \
+        rsync \
+        software-properties-common \
+        unzip \
+        zip \
+        zlib1g-dev \
+        wget \
+        vim \
+        nginx \
+        iputils-ping \
+        && \
+    rm -rf /var/lib/apt/lists/* && \
+    find /usr/local/cuda-9.0/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 curl -fSsL -O https://bootstrap.pypa.io/get-pip.py && \
+    python get-pip.py && \
+    rm get-pip.py
+
+RUN pip --no-cache-dir install \
+        numpy \
+        scipy \
+        sklearn \
+        pandas \
+        h5py
+
+# Set up grpc
+RUN pip install enum34 futures mock six && \
+    pip install --pre 'protobuf>=3.0.0a3' && \
+    pip install -i https://testpypi.python.org/simple --pre grpcio
+
+# Set up Bazel.
+
+# Running bazel inside a `docker build` command causes trouble, cf:
+#   https://github.com/bazelbuild/bazel/issues/134
+# The easiest solution is to set up a bazelrc file forcing --batch.
+RUN echo "startup --batch" >>/etc/bazel.bazelrc
+# Similarly, we need to workaround sandboxing issues:
+#   https://github.com/bazelbuild/bazel/issues/418
+RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone" \
+    >>/etc/bazel.bazelrc
+# Install the most recent bazel release which works: https://github.com/bazelbuild/bazel/issues/4652
+ENV BAZEL_VERSION 0.10.1
+WORKDIR /
+RUN mkdir /bazel && \
+    cd /bazel && \
+    curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
+    curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -o /bazel/LICENSE.txt https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE && \
+    chmod +x bazel-*.sh && \
+    ./bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
+    cd / && \
+    rm -f /bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh
+
+# Configure the build for our CUDA configuration.
+ENV CI_BUILD_PYTHON python
+ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
+ENV TF_NEED_CUDA 1
+ENV TF_CUDA_COMPUTE_CAPABILITIES=3.7,6.1
+ENV TF_CUDA_VERSION=9.0
+ENV TF_CUDNN_VERSION=7
+ENV CUDNN_INSTALL_PATH=/usr/lib/x86_64-linux-gnu
+
+ENV TF_SERVING_VERSION=1.7.0
+
+# Install tensorflow-serving-api
+RUN pip install tensorflow-serving-api==$TF_SERVING_VERSION
+
+# Download TensorFlow Serving
+RUN cd / && git clone --recurse-submodules https://github.com/tensorflow/serving && \
+  cd serving && \
+  git checkout $TF_SERVING_VERSION
+
+# Configure Tensorflow to use the GPU
+WORKDIR /serving
+RUN git clone --recursive https://github.com/tensorflow/tensorflow.git && \
+  cd tensorflow && \
+  git checkout v$TF_SERVING_VERSION && \
+  tensorflow/tools/ci_build/builds/configured GPU
+
+# Build TensorFlow Serving and Install it in /usr/local/bin
+WORKDIR /serving
+RUN bazel build -c opt --config=cuda \
+    --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" \
+    --crosstool_top=@local_config_cuda//crosstool:toolchain \
+    tensorflow_serving/model_servers:tensorflow_model_server && \
+    cp bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server /usr/local/bin/ && \
+    bazel clean --expunge
+
+# Update libstdc++6, as required by tensorflow-serving >= 1.6: https://github.com/tensorflow/serving/issues/819
+RUN add-apt-repository ppa:ubuntu-toolchain-r/test -y && \
+    apt-get update && \
+    apt-get install -y libstdc++6
+
+# cleaning up the container
+RUN rm -rf /serving && \
+    rm -rf /bazel
+

docker/1.7.0/final/py2/Dockerfile.cpu

@@ -0,0 +1,24 @@
+# Use local version of image built from Dockerfile.cpu in /docker/1.7.0/base
+FROM tensorflow-base:1.7.0-cpu-py2
+MAINTAINER Amazon AI
+
+ARG framework_installable
+ARG framework_support_installable=sagemaker_tensorflow_container-1.0.0.tar.gz
+
+WORKDIR /root
+
+# Will install from pypi once packages are released there. For now, copy from local file system.
+COPY $framework_installable .
+COPY $framework_support_installable .
+
+RUN framework_installable_local=$(basename $framework_installable) && \
+    framework_support_installable_local=$(basename $framework_support_installable) && \
+    \
+    pip install $framework_installable_local && \
+    pip install $framework_support_installable_local && \
+    \
+    rm $framework_installable_local && \
+    rm $framework_support_installable_local
+
+# entry.py comes from sagemaker-container-support
+ENTRYPOINT ["entry.py"]

docker/1.7.0/final/py2/Dockerfile.gpu

@@ -0,0 +1,25 @@
+# Use local version of image built from Dockerfile.gpu in /docker/1.6.0/base
+FROM tensorflow-base:1.7.0-gpu-py2
+MAINTAINER Amazon AI
+
+ARG framework_installable
+ARG framework_support_installable=sagemaker_tensorflow_container-1.0.0.tar.gz
+
+WORKDIR /root
+
+# Will install from pypi once packages are released there. For now, copy from local file system.
+COPY $framework_installable .
+COPY $framework_support_installable .
+
+RUN framework_installable_local=$(basename $framework_installable) && \
+    framework_support_installable_local=$(basename $framework_support_installable) && \
+    \
+    pip install $framework_installable_local && \
+    pip install $framework_support_installable_local && \
+    \
+    rm $framework_installable_local && \
+    rm $framework_support_installable_local
+
+# entry.py comes from sagemaker-container-support
+ENTRYPOINT ["entry.py"]
+

test/integ/test_versions.py

@@ -26,6 +26,9 @@ def required_versions(framework_version):
     elif framework_version == '1.6.0':
         return ['tensorflow-serving-api==1.5.0',
                 'tensorflow==1.6.0']
+    elif framework_version == '1.7.0':
+        return ['tensorflow-serving-api==1.7.0',
+                'tensorflow==1.7.0']
     else:
         raise ValueError("invalid internal test config")