ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  const std::vector<std::unique_ptr<ParallelTensor>>& handles = *outputs;
  std::vector<ParallelTensor*> handle_inputs;
  handle_inputs.reserve(handles.size());
  for (auto& handle : handles) {
    handle_inputs.push_back(handle.get());
  }
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> read_op(

// "Context" under which operations/functions are executed. It encapsulates
// things like the available devices, resource manager etc.
// TFE_Context must outlive all tensor handles created using it. In other
// words, TFE_DeleteContext() must be called after all tensor handles have
// been deleted (with TFE_DeleteTensorHandle).
//
// TODO(ashankar): Merge with TF_Session?
typedef struct TFE_Context TFE_Context;

	if err != nil {
		t.Fatal(err)
	}
}

// Test that the line splitter handles a final line without a newline.
func TestScanLineNoNewline(t *testing.T) {
	const text = "abcdefghijklmn\nopqrstuvwxyz"
	lines := []string{
		"abcdefghijklmn",
		"opqrstuvwxyz",
	}
	testNoNewline(text, lines, t)
}

// Test that the line splitter handles a final line with a carriage return but no newline.

// Create a packed TensorHandle with the given list of TensorHandles.
// If `handles` are on the same device, assign the same device to the packed
// handle; if `handles` are on different deivces, assign a CompositeDevice to
// it.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_CreatePackedTensorHandle(
    TFE_Context* ctx, TFE_TensorHandle** handles, int* num_handles,
    TF_Status* status);

			t.Fatalf("Test %d: Failed to create HTTP request for GetBucketPolicyHandler: <ERROR> %v", i+1, err)
		}
		// Since `apiRouter` satisfies `http.Handler` it has a ServeHTTP to execute the logic of the handler.
		// Call the ServeHTTP to execute the handler, GetBucketPolicyHandler handles the request.
		apiRouter.ServeHTTP(recV4, reqV4)
		// Assert the response code with the expected status.
		if recV4.Code != testCase.expectedRespStatus {

  // Pack 3 variable handles into one TFE_TensorHandle.
  // When remote is false, function device is placed on task0. Handle types are
  // REMOTE, REMOTE, LOCAL on task0. When remote is true, function device is
  // placed on task1, Handle types are LOCAL, REMOTE, LOCAL on task1.
  int num_replicas = 3;
  std::vector<TFE_TensorHandle*> handles = {h0, h1, h2};
  TFE_TensorHandle* packed_handle =

    tensorflow::ImmediateExecutionTensorHandle* unwrapped_handle =
        tensorflow::unwrap(handles[i]);
    if (tensorflow::CustomDeviceTensorHandle::classof(unwrapped_handle)) {
      // One of the inputs we're trying to pack is on a custom device. We'll let
      // the first custom device we see handle all of the packing.
      auto* custom_device_handle =

import org.apache.maven.model.building.ModelBuildingRequest;
import org.apache.maven.model.building.ModelProblemCollector;
import org.apache.maven.model.merge.MavenModelMerger;

/**
 * Handles profile injection into the model.
 *
 * @deprecated use {@link org.apache.maven.api.services.ModelBuilder} instead
 */
@Named
@Singleton
@Deprecated(since = "4.0.0")
@SuppressWarnings({"checkstyle:methodname"})

    return nullptr;
  }
  tensorflow::TensorHandle* handle =
      tensorflow::TensorHandleFromInterface(unwrapped_handle);

  if (handle->Type() != tensorflow::TensorHandle::LOCAL) {
    status->status = tensorflow::errors::InvalidArgument(
        "TFE_TensorHandleDevicePointer may not be called on a ",
        handle->TypeString(), " tensor handle.");
    return nullptr;

	}

	if len(subroute) == 0 {
		if m.handlers.hasAny(id) && !id.isTestHandler() {
			return fmt.Errorf("handler %v: %w", id.String(), ErrHandlerAlreadyExists)
		}

		m.handlers.single[id] = h
		return nil
	}
	subID := makeSubHandlerID(id, s)
	if m.handlers.hasSubhandler(subID) && !id.isTestHandler() {
		return fmt.Errorf("handler %v, subroute:%v: %w", id.String(), s, ErrHandlerAlreadyExists)
	}