struct stat st;
  if (stat(dst, &st) != 0) {
    if (errno != ENOENT) {
      TF_SetStatusFromIOError(status, errno, dst);
      return;
    }
  } else if (S_ISDIR(st.st_mode)) {
    TF_SetStatus(status, TF_FAILED_PRECONDITION, "target path is a directory");
    return;
  }

  // We cannot rename directories yet, so prevent this.
  if (stat(src, &st) != 0) {
    TF_SetStatusFromIOError(status, errno, src);

  if (!status->status.ok()) return nullptr;

  if (input_index >= op_def->input_arg_size() || input_index < 0) {
    status->status = tensorflow::errors::InvalidArgument(
        input_index, " out of range for ", op_name);
    return nullptr;
  }

  const tensorflow::OpDef_ArgDef& input_arg = op_def->input_arg()[input_index];

  if (input_arg.number_attr().empty()) {

  AbstractOperationPtr op(ctx->CreateOperation());
  TF_RETURN_IF_ERROR(op->Reset("ZerosLike", /*raw_device_name=*/nullptr));
  if (isa<tracing::TracingOperation>(op.get())) {
    TF_RETURN_IF_ERROR(dyn_cast<tracing::TracingOperation>(op.get())->SetOpName(
        absl::StrCat("ZerosLike", ToId(t)).c_str()));
  }
  TF_RETURN_IF_ERROR(op->AddInput(t));
  int num_outputs = 1;

  OwnedTFStatus c_status(TF_NewStatus());
  init_fn(&params, c_status.get());
  TF_RETURN_IF_ERROR(tsl::StatusFromTF_Status(c_status.get()));
  TF_RETURN_IF_ERROR(ValidateTPOptimizerRegistrationParams(params));
  TF_RETURN_IF_ERROR(ValidateTPOptimizer(optimizer));
  TF_RETURN_IF_ERROR(ValidateTPOptimizerConfigs(optimizer_configs));

  CGraphOptimizerRegister(

  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") {
    ctx.device_type = DLDeviceType::kDLCPU;
  } else if (device_type == "GPU") {
#if TENSORFLOW_USE_ROCM
    ctx.device_type = DLDeviceType::kDLROCM;
#else

  return op;
}

bool IsPlaceholder(const tensorflow::NodeDef& node_def) {
  if (node_def.op() != "Placeholder" || node_def.name() != "feed") {
    return false;
  }
  bool found_dtype = false;
  bool found_shape = false;
  for (const auto& attr : node_def.attr()) {
    if (attr.first == "dtype") {
      if (attr.second.type() == tensorflow::DT_INT32) {
        found_dtype = true;
      } else {

  if (TF_GetCode(status) != TF_OK) return;

  // unwrap op_ and set step_id only if valid step id value was set.
  // Currently only required for non-TFRT use cases, e.g., EagerOp.
  if (step_id_.has_value()) {
    tensorflow::unwrap(op_.get())->SetStepId(step_id_.value());
  }

  TFE_Execute(op_.get(), unwrapped_results.data(), &real_num_outputs, status);
  if (TF_GetCode(status) != TF_OK) {

      TFE_NewOp(context, "DestroyResourceOp", status), &TFE_DeleteOp);
  if (TF_GetCode(status) != TF_OK) return;
  TFE_OpAddInput(op.get(), handle_, status);
  if (TF_GetCode(status) != TF_OK) return;
  const char* device = TFE_TensorHandleDeviceName(handle_, status);
  if (TF_GetCode(status) != TF_OK) return;
  TFE_OpSetDevice(op.get(), device, status);
  if (TF_GetCode(status) != TF_OK) return;
  int num_retvals = 0;

  for (int i = 0; i < num_inputs; ++i) {
    TFE_TensorHandle* input = TFE_OpGetFlatInput(original_op, i, status);
    if (TF_GetCode(status) != TF_OK) return;
    const char* tensor_handle_device =
        TFE_TensorHandleDeviceName(input, status);
    if (TF_GetCode(status) != TF_OK) return;
    if (named_device->name() == tensor_handle_device) {
      // We assume that any tensors already placed on this device are

    Node* node = inputs[i].oper ? &inputs[i].oper->node : nullptr;
    int idx = inputs[i].index;

    TF_RETURN_WITH_CONTEXT_IF_ERROR(
        fn_body->graph.IsValidOutputTensor(node, idx),
        "Encountered while processing input ", i, " into function '", fn_name,
        "'");
    TF_RETURN_WITH_CONTEXT_IF_ERROR(ValidateNonRefOutput(node, idx),
                                    "Encountered while processing input ", i,