<li>Current HEAD Piper Changelist, if any: cl/${KOKORO_PIPER_CHANGELIST:-not available}</li>
<li>Pull Request Number, if any: ${KOKORO_GITHUB_PULL_REQUEST_NUMBER_tensorflow:- none}</li>
<li>Pull Request Link, if any: <a href="$KOKORO_GITHUB_PULL_REQUEST_URL_tensorflow">${KOKORO_GITHUB_PULL_REQUEST_URL_tensorflow:-none}</a></li>
<li>Commit: $KOKORO_GIT_COMMIT_tensorflow</li>
</ul>
<h2>Googlers-Only Links</h2>
<ul>

    _os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "1"):
  import tensorflow_io_gcs_filesystem as _tensorflow_io_gcs_filesystem

# Lazy-load Keras v1.
_tf_uses_legacy_keras = (
    _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1"))
setattr(_current_module, "keras", _KerasLazyLoader(globals(), mode="v1"))
_module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras")

# simple way to parameterize this from bazel, hence this helper to
# "normalize" the srcjar layout.
#
# Arguments:
#   src_jar - path to the original srcjar
#   dest_jar - path to the destination
# Returns:
#   None
function cp_normalized_srcjar() {
  src_jar="$1"
  dest_jar="$2"
  tmp_dir=$(mktemp -d)
  cp "${src_jar}" "${tmp_dir}/orig.jar"
  pushd "${tmp_dir}"
  # Extract any src/ files
  jar -xf "${tmp_dir}/orig.jar" src/

    _os.getenv("TF_USE_MODULAR_FILESYSTEM", "0") == "1"):
  import tensorflow_io_gcs_filesystem as _tensorflow_io_gcs_filesystem

# Lazy-load Keras v2/3.
_tf_uses_legacy_keras = (
    _os.environ.get("TF_USE_LEGACY_KERAS", None) in ("true", "True", "1"))
setattr(_current_module, "keras", _KerasLazyLoader(globals()))
_module_dir = _module_util.get_parent_dir_for_name("keras._tf_keras.keras")
_current_module.__path__ = [_module_dir] + _current_module.__path__

        "lib/gcc/arm-rpi-linux-gnueabihf/**",
        "include/**",
    ]),
)

filegroup(
    name = "aarch64_compiler_pieces",
    srcs = glob([
        "aarch64-none-linux-gnu/**",
        "libexec/**",
        "lib/gcc/aarch64-none-linux-gnu/**",
        "include/**",
    ]),
)

filegroup(
    name = "compiler_components",
    srcs = [
        ":ar",
        ":as",
        ":gcc",

  with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
    log_lines = f.read().splitlines()

  result_store_links: ResultDictType = {}
  current_url = None
  for i in range(len(log_lines)):
    line = log_lines[i]
    result_store_line_match = re.search(RESULT_STORE_LINK_RE, line)
    if not result_store_line_match:
      continue

*   TF Core:

    *   `tf.Graph.get_name_scope()` now always returns a string, as documented.
        Previously, when called within `name_scope("")` or `name_scope(None)`
        contexts, it returned `None`; now it returns the empty string.
    *   `tensorflow/core/ir/` contains a new MLIR-based Graph dialect that is
        isomorphic to GraphDef and will be used to replace GraphDef-based (e.g.,

**Raspberry Pi 2 and 3**      | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.html)           | [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv7l.whl)

    # copybara:comment_begin(OSS Windows only: DEF file for exported symbols)
    win_def_file = select({
        "//tensorflow:windows": ":tensorflow_filtered_def_file",
        "//conditions:default": None,
    }),
    # copybara:comment_end
    deps = [
        "//tensorflow/c:c_api",
        "//tensorflow/c:c_api_experimental",
        "//tensorflow/c:exported_symbols.lds",

/// TensorFlow checks that the plugin supplies all mandatory operations and
/// then copies these tables to a different memory location, marking the new
/// operation tables as read-only. Once a plugin is loaded, none of these
/// operation pointers may change.
///
/// There are 4 function tables: one for each of the 3 file objects in
/// TensorFlow (i.e., `RandomAccessFile`, `WritableFile`,