// Controls how to act when we try to run an operation on a given device but
// some input tensors are not on that device.
// LINT.IfChange
// Note: Keep in sync with internal copy of enum in eager/context.h.
typedef enum TFE_ContextDevicePlacementPolicy {
  // Running operations with input tensors on the wrong device will fail.
  TFE_DEVICE_PLACEMENT_EXPLICIT = 0,
  // Copy the tensor to the right device but log a warning.
  TFE_DEVICE_PLACEMENT_WARN = 1,

                      send_device.size());
  TFE_OpSetAttrString(op, "recv_device", recv_device.c_str(),
                      recv_device.size());
  TFE_OpSetAttrInt(op, "send_device_incarnation", send_device_incarnation);

  return op;
}

bool GetDeviceName(TFE_Context* ctx, string* device_name,
                   const char* device_type) {

                              const char* device_name, void* device_info,
                              TF_Status* status) {
  // Fill in default values for optional functionality.
  if (device.pack == nullptr) {
    device.pack = &DefaultCustomDevicePack;
  }
  auto custom_device = std::make_unique<tensorflow::CustomDeviceAPI>(
      ctx, device, device_info, device_name);

  // Check that copying it to the old remote device (named localhost) fails.
  TFE_TensorHandleCopyToDevice(h0_task0_new, ctx, remote_device_name, status);
  EXPECT_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Copying and executing on the new remote device works.
  const char new_remote_device_name[] =
      "/job:worker/replica:0/task:1/device:CPU:0";
  const char new_local_device_name[] =

  // returned by DeviceName should be "/device:GPU:*" until a particular GPU is
  // chosen for the operation by the device placement logic in the
  // executor. After that, the value returned by DeviceName will be a full
  // device name such as "/job:localhost/replica:0/task:0/device:GPU:1".
  virtual const string& DeviceName() const = 0;

  // Sets the operation device name.
  //

  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  const DLTensor* dltensor_out = &dlm_out->dl_tensor;
  EXPECT_EQ(dltensor_out->device.device_type, dltensor_in->device.device_type);
  EXPECT_EQ(dltensor_out->device.device_id, dltensor_in->device.device_id);
  EXPECT_EQ(dltensor_out->ndim, dltensor_in->ndim);
  EXPECT_EQ(dltensor_out->dtype.code, dltensor_in->dtype.code);

  DLDevice ctx;
  const char* device_name =
      tensorflow::unwrap(h)->BackingDeviceName(&status->status);
  DeviceNameUtils::ParsedName parsed_name;
  tensorflow::DeviceNameUtils::ParseFullName(device_name, &parsed_name);
  std::string device_type = parsed_name.type;
  int device_id = 0;
  if (parsed_name.has_id) {
    device_id = parsed_name.id;
  }

  ctx.device_id = device_id;
  if (device_type == "CPU") {

                                      DEVICE_CPU))));
}

TEST(TensorPjRtBufferUtilTest, GetPjRtCApiClientIncorrectType) {
  TF_ASSERT_OK_AND_ASSIGN(
      auto pjrt_client,
      xla::GetTfrtCpuClient(/*asynchronous=*/true, /*cpu_device_count=*/1));
  TF_ASSERT_OK(SetPjRtClientInTFGlobalResourceManager(DEVICE_CPU,
                                                      std::move(pjrt_client)));

			// - mount.Path doesn't match (means cross-device mount), should error out.
			if mount.Path != path {
				crossMounts = append(crossMounts, mount)
			}
		}
	}
	msg := `Cross-device mounts detected on path (%s) at following locations %s. Export path should not have any sub-mounts, refusing to start.`
	if len(crossMounts) > 0 {
		// if paths didn't match then we do have cross-device mount.
		return fmt.Errorf(msg, path, crossMounts)

  // Remote device on `worker1`.
  const char remote_device[] = "/job:localhost/replica:0/task:1/device:CPU:0";
  // `ctx_0`, `ctx_1`, `ctx_2` contains `remote_device`.
  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {