tensorflow serving目录解读
tf_serving-----WORKSPACE
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-----tensorflow-serving/----BUILD
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| -----workspace.bzl
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| -----example/-------BUILD
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| --------imagenet_lsvrc_2015_synsets.txt
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| --------imagenet_metadata.txt
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| --------inception_client.cc
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| --------inception_client.py
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| --------inception_k8s.yaml
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| --------inception_saved_model.py
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| --------mnist_client.py
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| --------mnist_iput_data.py
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| --------mnist_saved_model.py
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-----------tensorflow/-------BUILD
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| --------WORKSPACE
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| ----tensorflow/------BUILD
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| -------workspace.bzl
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-----------tf_models/----WORKSPACE
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-----official/
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-----tutorials/
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-----research/-------inception/-------------------WORKSPACE
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-------------------inception/--------BUILD
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---------inception_train.py
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---------inception_model.py
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---------inception_eval.py
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---------inception_distributed_train.py
解读：
项目文件夹名称为"tf_serving",WORKSPACE文件放在"tf_serving"项目文件夹的根目录
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tf_serving/WORKSPACE解读：
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#声明工作空间名称，与项目名称一致workspace(name = "tf_serving") #声明本地仓库'tensorflow'的名称及路径local_repository(name = "org_tensorflow", path = "tensorflow",)#声明io_bazel_rules_closurehttp_archive(……)#把新的Tensorflow Serving依赖加到workspace.bzlload("//tensorflow_serving:workspace.bzl","tf_serving_workspace")tf_serving_workspace()#指定bazel最低要求版本load("@org_tensorflow//tensorflow::workspace.bzl", "check_version")check_version("0.5.4")*************************************************************************
tf_serving/tensorflow_serving/workspace.bzl解读：
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#tensorFlow Serving外部依赖加载到WORKSPACE文件load('@org_tensorflow//tensorflow::workspace.bzl', 'tf_workspace')#此处是所有Tensorflow Serving的外部依赖。#workspace_dir是Tensorflow Serving repo的绝对路径，如果是作为submodule#连接，路径形式应该是'__workspace_dir__ + "serving"'def tf_serving_workspace(): native.new_local_repository( name = "inception_model", path = "tf_models/research/inception", build_file = "tf_models/research/inception/inception/BUILD", )tf_workspace(path_prefix = "", tf_repo_name = "org_tensorflow")#gRPC依赖native.bind(name = "libssl",actual = "@boringssl//:ssl",) native.bind( name = "zlib", actual = "@zlib_archive//:zlib")*************************************************************************
tf_serving/tensorflow_serving/BUILD解读：
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# Tensorflow serving描述package(default_visibility=["//tensorflow_serving:internal"],)licenses(["notice"])exports_files(["LICENSE"])#开放源代码标记package_group(name = "internal",package = ["//tensorflow_serving/...",],)filegroup(name = "all_files",srcs = glob(["**/*"],exclude = ["**/METADATA","**/OWNERS","g3doc/sitemap.md",],),)
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tf_serving/tensorflow/tensorflow/workspace.bzl解读：
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# 可以在WORKSPACE文件中加载的Tensorflow外部依赖load(……)def _is_windows():……def _get_env_var():……# 从'native.bazel_version'中解析bazel版本字符串def _parse_bazel_version():……# 检查正在使用指定版本的bazeldef check_version():……# 支持将Tensorflow作为submodule的临时工作区def _temp_workaround_http_archive_impl():……# 如果非零code退出，则执行指定参数的命令并调用'fail'def _execute_and_check_ret_code():……# 在仓库根目录应用补丁文件def _apply_patch():……# 下载仓库，在根节点应用补丁def _patched_http_archive_impl():……# 如果Tensorflow连接为submodule，path_prefix不再使用# tf_repo_name正在考虑中def tf_workspace():……
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tf_serving/tensorflow/tensorflow/BUILD解读：
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package(default_visibility = [":internal"])licenses(["notice"])exports_files(["LICENSE","ACKNOWLEDGMENTS",# leakr文件用于//third_party/cloud_tpu"leakr_badwords.dic","leakr_badfiles.dic",])load("//tensorflow:tensorflow.bzl", "tf_cc_shared_object")load("//tensorflow/core:platform/default/build_config.bzl", "tf_additional_binary_deps",)# 各种config settingconfig_setting()package_group()filegroup()py_library()filegroup(name = "all_opensource_files",data = [":all_files","//tensorflow/c:all_files","//tensorflow/cc:all_files",……],visibility = [':__subpackages__'],)load("//third_party/mkl:build_defs.bzl","if_mkl",)filegroup(name = "intel_binary_blob",data = if_mkl(["//third_party/mkl:intel_binary_blob",],),)filegroup(name = "docs_src",data = glob(["docs_src/**/*.md"]),)tf_cc_shared_object(……)
