"${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"

  # can't be set inside the rest of the _upload envs.
  FINAL_URI="$TFCI_ARTIFACT_FINAL_GCS_URI/$TF_VER_FULL"
  gsutil -m rsync -d -r "$DOWNLOADS" "$FINAL_URI"

  # Also mirror the latest-uploaded folder to the "latest" directory.
  # GCS does not support symlinks.
  gsutil -m rsync -d -r "$FINAL_URI" "$TFCI_ARTIFACT_LATEST_GCS_URI"
fi

if [[ "$TFCI_ARTIFACT_FINAL_PYPI_ENABLE" == 1 ]]; then

          absl::StrCat("The specified bucket gs://", bucket, " was not found.")
              .c_str());
    return result;
  }

  bool is_folder = FolderExists(gcs_file, path, status);
  if (TF_GetCode(status) != TF_OK) return false;
  if (is_folder) return true;

  bool is_object = ObjectExists(gcs_file, path, bucket, object, status);
  if (TF_GetCode(status) != TF_OK) return false;
  if (is_object) {

    "//tensorflow/tools/lib_package:jnilicenses_generate"
}

# This test ensures that all the targets built into the Python package include
# their dependencies. It's a rewritten version of the "smoke test", an older
# Python script that was very difficult to understand. See
# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/pip_smoke_test.py
@test "Pip package includes all required //tensorflow dependencies" {

semantics to match NumPy. * `tf.split` now takes arguments in a reversed order
and with different keywords. In particular, we now match NumPy order as
`tf.split(value, num_or_size_splits, axis)`. * `tf.sparse_split` now takes
arguments in reversed order and with different keywords. In particular we now
match NumPy order as `tf.sparse_split(sp_input, num_split, axis)`. NOTE: we have

//
// This has three benefits:
//   * allows having newer plugins than the current core TensorFlow: the
//     additional entries in the plugin's table are just discarded;
//   * allows having older plugins than the current core TensorFlow (though
//     we are still warning users): the entries that core TensorFlow expects
//     but plugins didn't provide will be set to `nullptr` values and core

   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
   ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
   WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE

    "//tensorflow/tools/lib_package:jnilicenses_generate"
}

# This test ensures that all the targets built into the Python package include
# their dependencies. It's a rewritten version of the "smoke test", an older
# Python script that was very difficult to understand. See
# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/pip_smoke_test.py
@test "Pip package includes all required //tensorflow dependencies" {

            all_valid = False
          if ver < 35:
            print('WARNING: XLA does not support CUDA compute capabilities '
                  'lower than sm_35. Disable XLA when running on older GPUs.')
      else:
        ver = float(m.group(0))
        if ver < 3.0:
          print('ERROR: TensorFlow only supports CUDA compute capabilities 3.0 '