absl::StrCat("ZerosLike", ToId(t)).c_str()));
  }
  TF_RETURN_IF_ERROR(op->AddInput(t));
  int num_outputs = 1;
  std::vector<AbstractTensorHandle*> outputs(num_outputs);
  TF_RETURN_IF_ERROR(
      op->Execute(absl::Span<AbstractTensorHandle*>(outputs), &num_outputs));
  *result = outputs[0];
  return absl::OkStatus();
}
}  // namespace

absl::Status GradientRegistry::Register(

  }
  std::vector<TFE_TensorHandle*> op_outputs(*num_outputs);
  TFE_Execute(op, op_outputs.data(), num_outputs, s);
  TFE_DeleteOp(op);
  if (TF_GetCode(s) != TF_OK) return;
  std::vector<TFE_TensorHandle*> unwrapped_outputs;
  unwrapped_outputs.reserve(op_outputs.size());
  for (auto* handle : op_outputs) {
    unwrapped_outputs.push_back(handle);
  }
  for (int i = 0; i < *num_outputs; ++i) {

          shape.dims()));
    }
    int num_outputs = 1;
    std::vector<AbstractTensorHandle*> outputs(num_outputs);
    TF_RETURN_IF_ERROR(operation->Execute(
        absl::Span<AbstractTensorHandle*>(outputs), &num_outputs));

    if (num_outputs != 1) {
      return errors::Internal("Expected 1 output but found ", num_outputs);
    }
    auto* t = dyn_cast<GraphTensor>(outputs[0]);
    if (!t) {

      inputs[edge->dst_input()] = {ToOperation(edge->src()),
                                   edge->src_output()};
    }
  }
}

int TF_OperationOutputNumConsumers(TF_Output oper_out) {
  int count = 0;
  for (const auto* edge : oper_out.oper->node.out_edges()) {
    if (edge->src_output() == oper_out.index) {
      ++count;
    }
  }
  return count;
}

  status->status = c.Run(op_reg_data->shape_inference_fn);
  if (!status->status.ok()) return;

  // Set output_shapes.
  TF_ShapeAndTypeList* output_shapes_result =
      TF_NewShapeAndTypeList(c.num_outputs());
  for (int i = 0; i < c.num_outputs(); ++i) {
    ShapeHandle shape_handle = c.output(i);
    TF_ShapeAndType& shape = output_shapes_result->items[i];
    shape.num_dims = c.Rank(shape_handle);