}

bool HasValidHardwareTarget(mlir::Operation* op) {
  // All TFLite ops has CPU interface, should be enough to check for cpu.
  return IsOpSupported(op, "CPU");
}

std::optional<std::string> GetDeviceName(mlir::Operation* op) {
  if (IsConst(op)) return std::nullopt;

  // The model may contain quant stats op which is unrelevant to the
  // execution.
  if (llvm::isa<mlir::func::ReturnOp, mlir::quantfork::StatisticsOp>(op))

                LOGGER.debug("Detected {}: {} from {} (remote: {})",
                    fileSystem.getFileSystemType(),
                    fileSystem.getMountPoint(),
                    fileSystem.getDeviceName(),
                    fileSystem.isRemote()
                );
                // We don't support network file systems
                if (fileSystem.isRemote()) {
                    return true;
                }

    ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  } else if (!async) {
    // Set the local device to CPU to easily validate mirroring
    string cpu_device_name;
    ASSERT_TRUE(GetDeviceName(ctx, &cpu_device_name, "CPU"));
    TFE_OpSetDevice(matmul, cpu_device_name.c_str(), status);
    EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
    auto remote_arg =

              TFE_TensorHandle* axis);

// If there is a device of type `device_type`, returns true
// and sets 'device_name' accordingly.
// `device_type` must be either "GPU" or "TPU".
bool GetDeviceName(TFE_Context* ctx, tensorflow::string* device_name,
                   const char* device_type);

// Create a ServerDef with the given `job_name` and add `num_tasks` tasks in it.

  TF_Tensor* t = TFE_TensorHandleResolve(hcpu, status.get());
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());

  // Disable the test if no GPU is present.
  string gpu_device_name;
  if (GetDeviceName(ctx, &gpu_device_name, "GPU")) {
    TFE_TensorHandle* hgpu = TFE_TensorHandleCopyToDevice(
        hcpu, ctx, gpu_device_name.c_str(), status.get());
    ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());

  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) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  ASSERT_EQ(0, device_id) << device_id;

  // Disable the test if no GPU is present.
  string gpu_device_name;
  if (GetDeviceName(ctx, &gpu_device_name, "GPU")) {
    TFE_TensorHandle* hgpu = TFE_TensorHandleCopyToDevice(
        hcpu, ctx, gpu_device_name.c_str(), status.get());