1. 技术文章
  2. bazel build tensorflow serving using with local downloaded tensorflow

bazel build tensorflow serving using with local downloaded tensorflow

由 删除回忆录丶 提交于 2021-01-27 14:10:14

问题


the tensorflow serving build denpend on large tensorflow; but i already build tensorflow successfully. so i want to use it. I do these things: I change the tensorflow serving 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")

But I build with this command error:

[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)

what shoud id do buil serving with locally tensorflow successfully? thank you!


回答1:


You should raise docker build ressource CPU and memory. I did a 4 vcpu and 4 Gig ram upgrade to docker on my laptop and but you need to cap Bazzel C compiler to 2048 Meg memory with this option when building tensorflow serving image

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 .

Also need to upgrade version of Bazel to 20 for build to work. in your docker file

Set up Bazel augmenter version 20 pour compiler 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

Here the whole docker file named dockerbuild.txt and the docker build command

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"]


来源：https://stackoverflow.com/questions/52436299/bazel-build-tensorflow-serving-using-with-local-downloaded-tensorflow

标签
tensorflow
bazel
serving
易学教程内所有资源均来自网络或用户发布的内容，如有违反法律规定的内容欢迎反馈！
该文章没有解决你所遇到的问题?点击提问,说说你的问题,让更多的人一起探讨吧!