seen = collections.Counter()
runfiles_matcher = re.compile(r"(/.*\.runfiles/)")


for f in files.strip().splitlines():
  # Just ignore any failures, they're probably not important
  try:
    r = JUnitXml.fromfile(f)
  except Exception as e:  # pylint: disable=broad-except
    print("Ignoring this XML parse failure in {}: ".format(f), str(e))

  source_file = re.search(
      r"/(bazel_pip|tensorflow)/.*", f.decode("utf-8")

            - `gcr.io/tensorflow-sigs/build:${{ github.event.number }}-python3.10`
            - `gcr.io/tensorflow-sigs/build:${{ github.event.number }}-python3.9`
            
            Re-apply the `build and push to gcr.io for staging` label to rebuild and push again. This comment will only be posted once.
      -
        name: Print image digest

# only on affected targets, usually. There are targets in //tensorflow/lite that
# don't pass --nobuild, so they're on their own.
#
# Although buildifier checks for formatting as well, "bazel build nobuild"
# checks for cross-file issues like bad includes or missing BUILD definitions.
#
# We can't test on the windows toolchains because they're using a legacy
# toolchain format (or something) that specifies the toolchain directly instead

_tf2.enable()

# API IMPORTS PLACEHOLDER

# WRAPPER_PLACEHOLDER

# Make sure directory containing top level submodules is in
# the __path__ so that "from tensorflow.foo import bar" works.
# We're using bitwise, but there's nothing special about that.
_API_MODULE = _sys.modules[__name__].bitwise
_tf_api_dir = _os.path.dirname(_os.path.dirname(_API_MODULE.__file__))
_current_module = _sys.modules[__name__]

// Core APIs
// -----------------------------------------------------------------------------

// A TF_ExecutionContext stores knowledge about how to execute an operation.
// E.g. it could know whether we're in eager mode or graph mode, keeps track
// of gradient tapes, etc.
typedef struct TF_ExecutionContext TF_ExecutionContext;

// A TF_AbstractTensor is an input to an operation. E.g. it could be a union

   "${TARGET}/usr/lib64"


# Link in architecture specific includes from the system; note that we cannot
# link in the whole aarch64-linux-gnu folder, as otherwise we're overlaying
# system gcc paths that we do not want to find.
# TODO(klimek): Automate linking in all non-gcc / non-kernel include
# directories.
mkdir -p "${TARGET}/usr/include/aarch64-linux-gnu"

# only on affected targets, usually. There are targets in //tensorflow/lite that
# don't pass --nobuild, so they're on their own.
#
# Although buildifier checks for formatting as well, "bazel build nobuild"
# checks for cross-file issues like bad includes or missing BUILD definitions.
#
# We can't test on the windows toolchains because they're using a legacy
# toolchain format (or something) that specifies the toolchain directly instead

  Otherwise your code may be broken by the change.

  """)

# Make sure directory containing top level submodules is in
# the __path__ so that "from tensorflow.foo import bar" works.
# We're using bitwise, but there's nothing special about that.
_API_MODULE = _sys.modules[__name__].bitwise  # pylint: disable=undefined-variable
_current_module = _sys.modules[__name__]

  """

  # First check to see if we're using a blessed version of the NDK.
  properties_path = '%s/source.properties' % android_ndk_home_path
  if is_windows() or is_cygwin():
    properties_path = cygpath(properties_path)
  with open(properties_path, 'r') as f:
    filedata = f.read()

  revision = re.search(r'Pkg.Revision = (\d+)', filedata)
  if revision:

  tensors.reserve(output_tensors.size());
  for (const TapeTensor& o : output_tensors) {
    // Note: the tensor can have already been watched and hence be in the tape,
    // so we cannot check that we're inserting it here.
    tensor_tape_[o.GetID()] = op_id;
    tensor_usage_[o.GetID()] = 1;
    tensors.push_back(o);
  }
  op_tape_[op_id] = OpTapeEntry<BackwardFunction, TapeTensor>{