tsl::Set_TF_Status_from_Status(status, v2_reader_->status());
      return;
    }
    auto result = BuildV2VarMaps();
    var_to_shape_map_.swap(result.first);
    var_to_data_type_map_.swap(result.second);
  } else {
    reader_.reset(new TensorSliceReader(filename));
    if (!reader_->status().ok()) {
      tsl::Set_TF_Status_from_Status(status, reader_->status());
      return;
    }
    var_to_shape_map_.reset(

        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f
      - name: Clean repository
        shell: bash

// Runs `model` maybe wrapped in a function call op. This can be thought as
// being equivalent to the following python code.
//
// if use_function:
//   outputs = tf.function(model)(inputs)
// else:
//   outputs = model(inputs)
Status RunModel(Model model, AbstractContext* ctx,
                absl::Span<AbstractTensorHandle* const> inputs,
                absl::Span<AbstractTensorHandle*> outputs, bool use_function);

        # To get the as-merged branch during the CI tests
        git diff --diff-filter ACMRT --name-only pull_branch^ pull_branch > $BATS_FILE_TMPDIR/changed_files
    else
        # If the branch is not present, then diff against origin/master
        git diff --diff-filter ACMRT --name-only origin/master > $BATS_FILE_TMPDIR/changed_files
    fi
}

    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),
                       /*use_function*/ ::testing::Values(true, false)));
#else
INSTANTIATE_TEST_SUITE_P(
    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),

      EXPECT_FALSE(found_placeholder);
      found_placeholder = true;
    } else if (oper == three) {
      EXPECT_FALSE(found_scalar_const);
      found_scalar_const = true;
    } else if (oper == add) {
      EXPECT_FALSE(found_add);
      found_add = true;
    } else if (oper == neg) {
      EXPECT_FALSE(found_neg);
      found_neg = true;
    } else {
      ASSERT_TRUE(GetNodeDef(oper, &node_def));

      EXPECT_EQ(orig_ptr, TF_TensorData(t));
    } else {
      // In async mode we expect forwarding to work without releasing the input
      // handle since by the time the kernel is executed we have released the
      // handle in the client code.
      EXPECT_EQ(orig_ptr, TF_TensorData(t));
    }
  } else {
    if (forward_input) {

  bool result;
  if (status == nullptr) {
    result = ops_->paths_exist(filesystem_.get(), translated_names.data(),
                               files.size(), nullptr);
  } else {
    std::vector<TF_Status*> plugin_status;
    plugin_status.reserve(files.size());
    for (int i = 0; i < files.size(); i++)
      plugin_status.push_back(TF_NewStatus());

            metadata.type = TF_ATTR_STRING;
          } else if (typestr == "list(int)") {
            metadata.type = TF_ATTR_INT;
          } else if (typestr == "list(float)") {
            metadata.type = TF_ATTR_FLOAT;
          } else if (typestr == "list(bool)") {
            metadata.type = TF_ATTR_BOOL;
          } else if (typestr == "list(type)") {
            metadata.type = TF_ATTR_TYPE;

_current_module.__path__ = [_module_dir] + _current_module.__path__
if _tf_uses_legacy_keras:
  _module_dir = _module_util.get_parent_dir_for_name("tf_keras.api._v1.keras")
else:
  _module_dir = _module_util.get_parent_dir_for_name("keras.api._v1.keras")
_current_module.__path__ = [_module_dir] + _current_module.__path__

_CONTRIB_WARNING = """