tfs:aarch64: add docker file to build aarch64 mkl configuration

tensorflow_serving/tools/docker/Dockerfile.devel-mkl-aarch64

@@ -0,0 +1,152 @@
+# Copyright 2022 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+ARG base_image="ubuntu:20.04"
+
+FROM "${base_image}" as base_build
+
+ARG TF_SERVING_VERSION_GIT_BRANCH=master
+ARG TF_SERVING_VERSION_GIT_COMMIT=HEAD
+
+ARG DEBIAN_FRONTEND=noninteractive
+
+LABEL maintainer="Sunita Nadampalli <[email protected]>"
+LABEL tensorflow_serving_github_branchtag=${TF_SERVING_VERSION_GIT_BRANCH}
+LABEL tensorflow_serving_github_commit=${TF_SERVING_VERSION_GIT_COMMIT}
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        automake \
+        build-essential \
+        ca-certificates \
+        curl \
+        git \
+        gcc-10 \
+        g++-10 \
+        libcurl3-dev \
+        libfreetype6-dev \
+        libpng-dev \
+        libtool \
+        libzmq3-dev \
+        mlocate \
+        openjdk-8-jdk\
+        openjdk-8-jre-headless \
+        pkg-config \
+        python-dev-is-python3 \
+        software-properties-common \
+        swig \
+        unzip \
+        wget \
+        zip \
+        zlib1g-dev \
+        python3-distutils \
+        && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py && \
+    python3 get-pip.py && \
+    rm get-pip.py
+
+#make gcc-10 the default version
+RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 1 && \
+    update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-10 1
+
+RUN pip3 --no-cache-dir install \
+    future>=0.17.1 \
+    grpcio \
+    h5py \
+    keras_applications>=1.0.8 \
+    keras_preprocessing>=1.1.0 \
+    mock \
+    numpy \
+    portpicker \
+    requests \
+    --ignore-installed six>=1.12.0
+
+# Set up Bazel
+ENV BAZEL_VERSION 5.1.1
+WORKDIR /
+RUN mkdir /bazel && \
+    cd /bazel && \
+    wget https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-linux-arm64 && \
+    mv bazel-$BAZEL_VERSION-linux-arm64 bazel && \
+    chmod a+x bazel
+    ENV PATH=$WORKDIR/bazel:$PATH
+
+# Download TF Serving sources (optionally at specific commit).
+WORKDIR /tensorflow-serving
+RUN curl -sSL --retry 5 https://github.com/tensorflow/serving/tarball/${TF_SERVING_VERSION_GIT_COMMIT} | tar --strip-components=1 -xzf -
+
+FROM base_build as binary_build
+# Build, and install TensorFlow Serving
+ARG TF_SERVING_BUILD_OPTIONS="--config=mkl_aarch64 --copt=-Wno-maybe-uninitialized --copt=-Wno-error=stringop-truncation"
+
+RUN echo "Building with build options: ${TF_SERVING_BUILD_OPTIONS}"
+ARG TF_SERVING_BAZEL_OPTIONS=""
+RUN echo "Building with Bazel options: ${TF_SERVING_BAZEL_OPTIONS}"
+
+RUN bazel build --color=yes --curses=yes \
+    ${TF_SERVING_BAZEL_OPTIONS} \
+    --verbose_failures \
+    --output_filter=DONT_MATCH_ANYTHING \
+    ${TF_SERVING_BUILD_OPTIONS} \
+    tensorflow_serving/model_servers:tensorflow_model_server && \
+    cp bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server \
+    /usr/local/bin/
+
+# Build and install TensorFlow Serving API
+RUN bazel build --color=yes --curses=yes \
+    ${TF_SERVING_BAZEL_OPTIONS} \
+    --verbose_failures \
+    --output_filter=DONT_MATCH_ANYTHING \
+    ${TF_SERVING_BUILD_OPTIONS} \
+    tensorflow_serving/tools/pip_package:build_pip_package && \
+    bazel-bin/tensorflow_serving/tools/pip_package/build_pip_package \
+    /tmp/pip && \
+    pip --no-cache-dir install --no-dependencies --upgrade \
+    /tmp/pip/tensorflow_serving_api-*.whl && \
+    rm -rf /tmp/pip
+
+# Expose ports
+# gRPC
+EXPOSE 8500
+
+# REST
+EXPOSE 8501
+
+# Set where models should be stored in the container
+ENV MODEL_BASE_PATH=/models
+RUN mkdir -p ${MODEL_BASE_PATH}
+
+# The only required piece is the model name in order to differentiate endpoints
+ENV MODEL_NAME=model
+
+# Create a script that runs the model server so we can use environment variables
+# while also passing in arguments from the docker command line
+RUN echo '#!/bin/bash \n\n\
+tensorflow_model_server --port=8500 --rest_api_port=8501 \
+--model_name=${MODEL_NAME} --model_base_path=${MODEL_BASE_PATH}/${MODEL_NAME} \
+"$@"' > /usr/bin/tf_serving_entrypoint.sh \
+&& chmod +x /usr/bin/tf_serving_entrypoint.sh
+
+ENTRYPOINT ["/usr/bin/tf_serving_entrypoint.sh"]
+
+
+ENV LIBRARY_PATH '/usr/local/lib:$LIBRARY_PATH'
+ENV LD_LIBRARY_PATH '/usr/local/lib:$LD_LIBRARY_PATH'
+
+FROM binary_build as clean_build
+# Clean up Bazel cache when done.
+RUN bazel clean --expunge --color=yes && \
+    rm -rf /root/.cache
+CMD ["/bin/bash"]