tensorflow - bazel 使用本地下载的 tensorflow 构建 tensorflow 服务

Question

tensorflow 服务构建依赖于大型 tensorflow；但我已经成功构建了 tensorflow。所以我想用它。我做这些事情：我改变了 tensorflow 服务 WORKSPACE(org: https://github.com/tensorflow/serving/blob/master/WORKSPACE )

workspace(name = "tf_serving")

# To update TensorFlow to a new revision.
# 1. Update the 'git_commit' args below to include the new git hash.
# 2. Get the sha256 hash of the archive with a command such as...
#    curl -L https://github.com/tensorflow/tensorflow/archive/<git hash>.tar.gz | sha256sum
#    and update the 'sha256' arg with the result.
# 3. Request the new archive to be mirrored on mirror.bazel.build for more
#    reliable downloads.
#load("//tensorflow_serving:repo.bzl", "tensorflow_http_archive")

#tensorflow_http_archive(
#    name = "org_tensorflow",
#    sha256 = "0f4b8375de30c54cc3233bc40e04742dab0ffe007acf8391651c6adb62be89f8",
#    git_commit = "2ea398b12ed18b6c51e09f363021c6aa306c5179",
#)

local_repository(
    name = "org_tensorflow",
    path = "/vagrant/tf/tensorflow/",
)


# TensorFlow depends on "io_bazel_rules_closure" so we need this here.
# Needs to be kept in sync with the same target in TensorFlow's WORKSPACE file.
http_archive(
    name = "io_bazel_rules_closure",
    sha256 = "a38539c5b5c358548e75b44141b4ab637bba7c4dc02b46b1f62a96d6433f56ae",
    strip_prefix = "rules_closure-dbb96841cc0a5fb2664c37822803b06dab20c7d1",
    urls = [
        "https://mirror.bazel.build/github.com/bazelbuild/rules_closure/archive/dbb96841cc0a5fb2664c37822803b06dab20c7d1.tar.gz",
        "https://github.com/bazelbuild/rules_closure/archive/dbb96841cc0a5fb2664c37822803b06dab20c7d1.tar.gz",  # 2018-04-13
    ],
)

# Please add all new TensorFlow Serving dependencies in workspace.bzl.
load("//tensorflow_serving:workspace.bzl", "tf_serving_workspace")

tf_serving_workspace()

# Specify the minimum required bazel version.
load("@org_tensorflow//tensorflow:version_check.bzl", "check_bazel_version_at_least")

check_bazel_version_at_least("0.15.0")

但我用这个命令错误构建：

[root@localhost serving]# tools/bazel_in_docker.sh bazel build --config=nativeopt tensorflow_serving/...
== Pulling docker image: tensorflow/serving:nightly-devel
Trying to pull repository docker.io/tensorflow/serving ...
nightly-devel: Pulling from docker.io/tensorflow/serving
Digest: sha256:f500ae4ab367cbabfd474487175bb357d73c01466a80c699db90ba3f0ba7b5a8
Status: Image is up to date for docker.io/tensorflow/serving:nightly-devel
== Running cmd: sh -c 'cd /root/serving; TEST_TMPDIR=.cache bazel build --config=nativeopt tensorflow_serving/...'
usermod: no changes
$TEST_TMPDIR defined: output root default is '/root/serving/.cache' and max_idle_secs default is '15'.
Starting local Bazel server and connecting to it...
.............
ERROR: error loading package '': Encountered error while reading extension file 'tensorflow/workspace.bzl': no such package '@org_tensorflow//tensorflow': /root/serving/.cache/_bazel_root/01a289b7faaf5ec651fb0e4e35f862a1/external/org_tensorflow must be an existing directory
ERROR: error loading package '': Encountered error while reading extension file 'tensorflow/workspace.bzl': no such package '@org_tensorflow//tensorflow': /root/serving/.cache/_bazel_root/01a289b7faaf5ec651fb0e4e35f862a1/external/org_tensorflow must be an existing directory
INFO: Elapsed time: 0.460s
INFO: 0 processes.
FAILED: Build did NOT complete successfully (0 packages loaded)

应该如何使用本地 tensorflow 成功构建服务？谢谢你！

score 0 · Accepted Answer

您应该提高 docker build ressource CPU 和内存。我在笔记本电脑上对 docker 进行了 4 vcpu 和 4 Gig ram 升级，但是在构建 tensorflow 服务映像时，您需要使用此选项将 Bazzel C 编译器限制为 2048 Meg 内存

https://www.tensorflow.org/serving/docker

docker build --pull --build-arg TF_SERVING_BUILD_OPTIONS="--copt=-mavx \
  --cxxopt=-D_GLIBCXX_USE_CXX11_ABI=0 --local_resources 2048,.5,1.0" -t \
  $USER/tensorflow-serving-devel -f Dockerfile.devel .

还需要将 Bazel 的版本升级到 20 才能使构建工作。在你的码头文件

设置 Bazel augmenter 版本 20 倒编译器 tensorflow

  

   Set up Bazel augmenter version 20 pour compiler tensorflow
    # Need >= 0.15.0 so bazel compiles work with docker bind mounts.
    ENV BAZEL_VERSION 0.20.0
    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

这里是名为 dockerbuild.txt 的整个 docker 文件和 docker build 命令

docker build --pull --build-arg TF_SERVING_BUILD_OPTIONS="--copt=-mavx --cxxopt=-D_GLIBCXX_USE_CXX11_ABI=0 --local_resources 2048,.5,1.0" -f dockerbuild.txt 。

# Copyright 2018 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.
FROM ubuntu:18.04 as base_build

ARG TF_SERVING_VERSION_GIT_BRANCH=master
ARG TF_SERVING_VERSION_GIT_COMMIT=head

LABEL maintainer=gvasudevan@google.com
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 \
        libcurl3-dev \
        libfreetype6-dev \
        libpng-dev \
        libtool \
        libzmq3-dev \
        mlocate \
        openjdk-8-jdk\
        openjdk-8-jre-headless \
        pkg-config \
        python-dev \
        software-properties-common \
        swig \
        unzip \
        wget \
        zip \
        zlib1g-dev \
        && \
    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 \
    grpcio \
	h5py \
    keras_applications \
    keras_preprocessing \
    mock \
    numpy \
	six	  \
	Pillow \ 
	matplotlib \
	opencv-python \ 
	pandas \ 
    requests 


# Set up Bazel augmenter version 20 pour compiler tensorflow
# Need >= 0.15.0 so bazel compiles work with docker bind mounts.
ENV BAZEL_VERSION 0.20.0
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

# Download TF Serving sources (optionally at specific commit).
WORKDIR /tensorflow-serving
RUN git clone --branch=${TF_SERVING_VERSION_GIT_BRANCH} https://github.com/tensorflow/serving . && \
    git remote add upstream https://github.com/tensorflow/serving.git && \
    if [ "${TF_SERVING_VERSION_GIT_COMMIT}" != "head" ]; then git checkout ${TF_SERVING_VERSION_GIT_COMMIT} ; fi


FROM base_build as binary_build
# Build, and install TensorFlow Serving
ARG TF_SERVING_BUILD_OPTIONS="--config=nativeopt"
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 --upgrade \
    /tmp/pip/tensorflow_serving_api-*.whl && \
    rm -rf /tmp/pip

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"]

tensorflow - bazel 使用本地下载的 tensorflow 构建 tensorflow 服务

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