absl::optional<int64_t> step_id) const {
  for (int device_index = 0; device_index < underlying_devices_.size();
       ++device_index) {
    DeviceThread* device_thread = device_threads_[device_index].get();
    std::vector<TFE_TensorHandle*> device_inputs;
    device_inputs.reserve(inputs.size());
    for (int input_index = 0; input_index < inputs.size(); ++input_index) {

              StatusIs(error::INTERNAL,
                       HasSubstr(absl::StrCat("PjRtClient for ", DEVICE_CPU,
                                              " is not type PjRtCApiClient"))));
}

TEST(TensorPjRtBufferUtilTest, GetPjRtCApiClientSuccess) {
  auto status = pjrt::PjrtApi(DEVICE_CPU);
  if (!status.ok()) {
    TF_ASSERT_OK(pjrt::SetPjrtApi(DEVICE_CPU, GetPjrtApi()));
  }

                      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) {

  TensorHandleSilentCopy(false, TFE_DEVICE_PLACEMENT_SILENT,
                         TFE_DEVICE_PLACEMENT_SILENT, false);
}
TEST(CAPI, TensorHandleSilentCopyAsync) {
  TensorHandleSilentCopy(true, TFE_DEVICE_PLACEMENT_SILENT,
                         TFE_DEVICE_PLACEMENT_SILENT, false);
}
TEST(CAPI, TensorHandleSilentCopyLocalPolicy) {
  TensorHandleSilentCopy(false, TFE_DEVICE_PLACEMENT_EXPLICIT,

//
// `device_name` must not name an existing physical or custom device. It must
// follow the format:
//
//    /job:<name>/replica:<replica>/task:<task>/device:<type>:<device_num>
//
// If the device is successfully registered, `status` is set to TF_OK. Otherwise
// the device is not usable. In case of a bad status, `device.delete_device` is
// still called on `device_info` (i.e. the caller does not retain ownership).

  const char* device_type = TFE_TensorHandleDeviceType(hcpu, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  ASSERT_TRUE(absl::StrContains(device_type, "CPU")) << device_type;
  int device_id = TFE_TensorHandleDeviceID(hcpu, status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  ASSERT_EQ(0, device_id) << device_id;

                              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);

  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_PLACEMENT_WARN = 1,
  // Silently copy the tensor, which has a performance cost since the operation
  // will be blocked till the copy completes. This is the default policy.
  DEVICE_PLACEMENT_SILENT = 2,
  // Placement policy which silently copies int32 tensors but not other dtypes.
  DEVICE_PLACEMENT_SILENT_FOR_INT32 = 3,
};
// LINT.ThenChange(//tensorflow/c/eager/c_api.h)

# tensorflow/python:_pywrap_parallel_device.
filegroup(
    name = "lib_headers",
    srcs = ["parallel_device_lib.h"],
)

filegroup(
    name = "lib_sources",
    srcs = ["parallel_device_lib.cc"],
)

filegroup(
    name = "device_headers",
    srcs = ["parallel_device.h"],
)

filegroup(
    name = "device_sources",
    srcs = ["parallel_device.cc"],
)

filegroup(
    name = "headers",