(*var_to_data_type_map)[key] = DataType(entry.dtype());
  }
  // The returned pointers are owned by the caller.
  return std::make_pair(std::move(var_to_shape_map),
                        std::move(var_to_data_type_map));
}

}  // namespace checkpoint

      info->ops[index].scheme,
      std::make_unique<tensorflow::ModularFileSystem>(
          std::move(filesystem), std::move(core_filesystem_ops),
          std::move(core_random_access_file_ops),
          std::move(core_writable_file_ops),
          std::move(core_read_only_memory_region_ops),
          info->plugin_memory_allocate, info->plugin_memory_free));
}

    }
}


private
fun IntegrationTest.addDebugProperties() {
    // TODO Move magic property out
    if (project.hasProperty("org.gradle.integtest.debug")) {
        systemProperties["org.gradle.integtest.debug"] = "true"
        testLogging.showStandardStreams = true
    }
    // TODO Move magic property out
    if (project.hasProperty("org.gradle.integtest.verbose")) {

"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied.  See the License for the
specific language governing permissions and limitations
under the License.
-->

<project>
    <!-- once we move past supporting modelVersion 4.0.0 we should update this version -->
    <modelVersion>3.9.9</modelVersion>
    <groupId>tests.project</groupId>
    <artifactId>past-model-version</artifactId>
    <version>1</version>

  if (av_tensor == nullptr) {
    TF_ASSIGN_OR_RETURN(
        *tensor, MakeTensorFromPjRtBuffer(tensor->dtype(), tensor->shape(),
                                          std::move(buffer)));
  } else {
    av_tensor->SetBuffer(std::move(buffer));
  }
  return absl::OkStatus();
}

absl::StatusOr<xla::PjRtCApiClient*> GetPjRtCApiClient(
    const DeviceType& device_type) {

      : device_(device),
        tensors_(std::move(tensors)),
        shape_(std::vector<int64_t>(shape.begin(), shape.end())),
        dtype_(dtype) {}
  ParallelTensor(const ParallelDevice& device,
                 std::vector<TensorHandlePtr> tensors, const TF_DataType dtype)
      : device_(device),
        tensors_(std::move(tensors)),
        shape_(absl::nullopt),
        dtype_(dtype) {}

  fun invalidatesCache(method: String): Boolean =
    (
      method == "POST" || method == "PATCH" || method == "PUT" ||
        method == "DELETE" || method == "MOVE"
    )

  @JvmStatic // Despite being 'internal', this method is called by popular 3rd party SDKs.
  fun requiresRequestBody(method: String): Boolean =
    (
      method == "POST" || method == "PUT" ||

    }
  }

  TF_DeleteTensor(analytical_tensor);
  delete[] danalytical;
}

Model BuildGradModel(Model forward, GradientRegistry registry) {
  return [forward_model = std::move(forward),
          grad_registry = std::move(registry)](
             AbstractContext* ctx,
             absl::Span<AbstractTensorHandle* const> inputs,
             absl::Span<AbstractTensorHandle*> outputs) -> Status {

set -euxo pipefail

cd "$TFCI_OUTPUT_DIR"

# Move extra wheel files somewhere out of the way. This script
# expects just one wheel file to exist.
if [[ "$(ls *.whl | wc -l | tr -d ' ')" != "1" ]]; then
  echo "More than one wheel file is present: moving the oldest to"
  echo "$TFCI_OUTPUT_DIR/extra_wheels."
  # List all .whl files by their modification time (ls -t) and move anything

          {std::move(bucket), std::move(object), &gcs_file->gcs_client,
           TempFile(temp_file_name, std::ios::binary | std::ios::trunc), false,
           static_cast<int64_t>(metadata->size())});
    } else if (TF_GetCode(status) == TF_NOT_FOUND) {
      file->plugin_file = new tf_writable_file::GCSFile(
          {std::move(bucket), std::move(object), &gcs_file->gcs_client,