op->emitError() << "TPUCopyWithDynamicShapeOp is not in a launch";
  }
  std::string device_str = launch_op.getDeviceAttr().getValue().str();
  std::string cpu0_device;
  if (failed(tensorflow::GetNonReplicatedCPU0(op, &cpu0_device)))
    return failure();
  if (device_str != tensorflow::GetDeviceAliasForHostOfLogicalCore(0) &&
      device_str != cpu0_device) {
    op->emitError()

  auto device_attr = op->getAttrOfType<StringAttr>("device");
  if (!device_attr || device_attr.getValue().empty()) return device_ordinal_str;

  // TODO(b/229028654) Remove string conversion once implicit conversion between
  // llvm::StringRef and absl::string_view works.
  absl::string_view device_str(device_attr.data(), device_attr.size());

                       SP_DeviceMemoryBase* const device_dst,
                       const SP_DeviceMemoryBase* const device_src,
                       uint64_t size, TF_Status* const status) {
    TF_SetStatus(status, TF_OK, "");
    std::memcpy(device_dst->opaque, device_src->opaque, size);
  };

  StreamExecutor* executor = GetExecutor(0);

                      ::testing::EquivToProto(original_graph_def)));
#endif
  }

  void InitGraphOptions() {
    session_options_.config = config_proto_;
    graph_optimization_pass_options_.device_set = &device_set_;
    graph_optimization_pass_options_.session_options = &session_options_;
    graph_optimization_pass_options_.graph = &graph_;
    graph_optimization_pass_options_.flib_def = flib_.get();
  }

void MemcpyDToH(const SP_Device* const device, SP_Stream stream, void* host_dst,
                const SP_DeviceMemoryBase* const device_src, uint64_t size,
                TF_Status* const status) {}
void MemcpyHToD(const SP_Device* const device, SP_Stream stream,
                SP_DeviceMemoryBase* const device_dst, const void* host_src,
                uint64_t size, TF_Status* const status) {}

                      const SP_DeviceMemoryBase* device_src, uint64_t size,
                      TF_Status* status);

  // Enqueues a memcpy operation onto stream, with a device destination
  // location and a host memory source, with target size `size`.
  void (*memcpy_htod)(const SP_Device* device, SP_Stream stream,
                      SP_DeviceMemoryBase* device_dst, const void* host_src,

  auto device_attr =
      func.getArgAttrOfType<mlir::StringAttr>(arg_no, kFuncDeviceAttr);
  return device_attr ? device_attr.getValue() : "";
}

// Extracts and canonicalizes the device attribute.
inline StringRef GetDeviceAttr(Operation* op) {
  auto device_attr = op->getAttrOfType<mlir::StringAttr>(kDeviceAttr);
  return device_attr ? device_attr.getValue() : "";
}

      // If op already has a TPU device set, simply propagate its device.
      auto device_attr = op_to_update->getAttrOfType<StringAttr>(kDeviceAttr);
      const bool has_device = device_attr && !device_attr.getValue().empty();
      if (has_device && tensorflow::IsTPUDevice(device_attr.getValue())) {
        PopulateDeviceForOpResults(*op_to_update, device_attr.getValue(),
                                   value_to_device);
        continue;

      mlir::Operation *user_op = use.getOwner();
      StringAttr device_attr = user_op->getAttrOfType<StringAttr>(kDeviceAttr);
      if (!device_attr) {
        all_uses_replaced = false;
        continue;
      }
      // Cloned the ConstOp and set its device attribute to be the same as the
      // device of the user operation.
      if (cloned_op_by_device.find(device_attr.getValue()) ==
          cloned_op_by_device.end()) {

// prevent it from running on GPU device.
bool CanUseGpuDevice(Operation *op) {
  auto device_attr = op->getAttrOfType<StringAttr>("device");
  if (!device_attr || device_attr.getValue().empty()) return true;

  DeviceNameUtils::ParsedName device;
  if (!DeviceNameUtils::ParseFullName(device_attr.getValue().str(), &device))
    return false;

  // We can't use GPU if operation explicitly placed on non-GPU device.