title: bazel build tensorflow serving using with local downloaded tensorflow
body: <p>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: <a href="https://github.com/tensorflow/serving/blob/master/WORKSPACE" rel="nofollow noreferrer">https://github.com/tensorflow/serving/blob/master/WORKSPACE</a>)</p>
  
  <pre><code>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/&lt;git hash&gt;.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")
  </code></pre>
  
  <p>But I build with this command error:</p>
  
  <pre><code>[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)
  </code></pre>
  
  <p>what shoud id do buil serving with locally tensorflow successfully? thank you!</p>