// per-device tensors.
    OpPtr op(TFE_NewOp(context, operation_name, status));
    TFE_OpAddAttrs(op.get(), attributes);
    int expected_outputs = TFE_OpGetOutputLength(op.get(), "outputs", status);
    if (TF_GetCode(status) != TF_OK) return result;
    if (expected_outputs != parallel_device.num_underlying_devices()) {
      std::string message(absl::StrCat(

  // Try to retrieve lengths before building the attributes (should fail)
  EXPECT_EQ(-1, TFE_OpGetInputLength(identityOp, "input", status));
  CHECK_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);
  EXPECT_EQ(-1, TFE_OpGetOutputLength(identityOp, "output", status));
  CHECK_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);

  TFE_TensorHandle* inputs[] = {input1, input2};
  TFE_OpAddInputList(identityOp, inputs, 2, status);

                                               TF_Status* status);

// Returns the length (number of tensors) of the output argument `output_name`
// found in the provided `op`.
TF_CAPI_EXPORT extern int TFE_OpGetOutputLength(TFE_Op* op,
                                                const char* output_name,
                                                TF_Status* status);

                                               TF_Status* status) {
  int ret = -1;
  status->status = tensorflow::unwrap(op)->InputLength(input_name, &ret);
  return ret;
}

TF_CAPI_EXPORT extern int TFE_OpGetOutputLength(TFE_Op* op,
                                                const char* output_name,
                                                TF_Status* status) {
  int ret = -1;