)

# Add Keras module aliases
_losses = _KerasLazyLoader(globals(), submodule="losses", name="losses")
_metrics = _KerasLazyLoader(globals(), submodule="metrics", name="metrics")
_optimizers = _KerasLazyLoader(
    globals(), submodule="optimizers", name="optimizers")
_initializers = _KerasLazyLoader(
    globals(), submodule="initializers", name="initializers")
setattr(_current_module, "losses", _losses)

TFCI_ARTIFACT_FINAL_GCS_URI="gs://tensorflow/versions/"
TFCI_ARTIFACT_FINAL_PYPI_ARGS="--config-file=$KOKORO_KEYSTORE_DIR/73361_tensorflow_pypirc_using_global_api_token --repository pypi-warehouse"
TFCI_ARTIFACT_FINAL_PYPI_ENABLE=1
TFCI_ARTIFACT_LATEST_GCS_URI="gs://tensorflow/versions/latest/"
TFCI_ARTIFACT_STAGING_GCS_ENABLE=1

# 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")
_current_module.__path__ = [_module_dir] + _current_module.__path__
if _tf_uses_legacy_keras:

          NodeDef* const node_def = graph_def.add_node();
          *node_def = node->def();
        }
      }
      *graph_def.mutable_library() = graph.flib_def().ToProto();
      if (flags::Global().more_stack_traces.value()) {
        *graph_def.mutable_debug_info() = graph.BuildDebugInfo();
      }
      session->graph->mu.unlock();
      status->status = session->session->Extend(std::move(graph_def));

TFCI_ARTIFACT_FINAL_GCS_URI="gs://tensorflow/nightly/"
TFCI_ARTIFACT_FINAL_PYPI_ARGS="--config-file=$KOKORO_KEYSTORE_DIR/73361_tensorflow_pypirc_using_global_api_token --repository pypi-warehouse"
TFCI_ARTIFACT_FINAL_PYPI_ENABLE=1
TFCI_ARTIFACT_LATEST_GCS_URI="gs://tensorflow/nightly/latest/"
TFCI_ARTIFACT_STAGING_GCS_ENABLE=1

setup_file() {
    cd /tf/tensorflow
    bazel version  # Start the bazel server
    # Without this, git errors if /tf/tensorflow directory owner is different
    git config --global --add safe.directory /tf/tensorflow
    # Note that you could generate a list of all the affected targets with e.g.:
    # bazel query $(paste -sd "+" $BATS_FILE_TMPDIR/changed_files) --keep_going

  string actual_string(reinterpret_cast<const char*>(op_buf->data),
                       op_buf->length);
  ASSERT_EQ(TF_OK, TF_GetCode(status));

  const OpDef* expected_op_def;
  TF_ASSERT_OK(OpRegistry::Global()->LookUpOpDef("Add", &expected_op_def));
  string expected_serialized;
  expected_op_def->SerializeToString(&expected_serialized);
  EXPECT_EQ(expected_serialized, actual_string);
  TF_DeleteBuffer(g_buf);

  // used to cancel all other operations if any fails.
  //
  // Set step_id to configure the step id used for rendezvous creation. step id
  // of value -1 is reserved for global rendezvous and should not be set here.
  void StartExecute(TFE_Context* context,
                    const std::vector<ParallelTensor*>& inputs,
                    const char* operation_name, const TFE_OpAttrs* attributes,

    }
    return tensorflow::errors::Internal("Graph pass runs for more than once!");
  }

 private:
  bool first_call_ = true;
};

// After the graph pass is registered, it takes effect globally and can affect
// other test cases. Define a static variable to switch it on and off.
bool GraphErrorInjectionPass::enabled_ = false;

// Test to ensure that a registered graph optimization pass is only executed

    tensorflow::MarkForCompilationPassFlags* flags =
        tensorflow::GetMarkForCompilationPassFlags();
    flags->tf_xla_cpu_global_jit = true;
    flags->tf_xla_min_cluster_size = 1;
  } else {
    optimizer_options->set_global_jit_level(tensorflow::OptimizerOptions::OFF);
  }
}

unsigned char TF_SetXlaEnableLazyCompilation(unsigned char enable) {
  tensorflow::BuildXlaOpsPassFlags* flags =