TF_NewStatus(), TF_DeleteStatus);

  // Start a new function / execution context.
  string fn_name = "double";
  TF_ExecutionContext* graph_ctx =
      TF_CreateFunction(fn_name.c_str(), status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  auto* placeholder_t =
      TF_AddFunctionParameter(graph_ctx, TF_FLOAT, {-1, nullptr}, status.get());

bool TF_StringStreamNext(TF_StringStream* list, const char** result) {
  if (list->position >= list->list->size()) {
    *result = nullptr;
    return false;
  }

  *result = list->list->at(list->position++).c_str();
  return true;
}

void TF_StringStreamDone(TF_StringStream* list) {
  delete list->list;
  delete list;
}
TF_StringStream* TF_GetChildren(const char* dirname, TF_Status* status) {

 private:
  // Whether to run this pass. If this is enabled, the NodeDef will be imported
  // to MLIR even no tf composition file is found.
  bool IsEnabled() {
    const char* tfr_lib_env_val = getenv(string(kTFRLibEnv).c_str());
    return tfr_lib_env_val != nullptr;
  }
};

}  // namespace tfr
}  // namespace tensorflow

    std::string flops_str;
    std::string mac_str;
    if (ops_count < 10000) {
      flops_str = absl::StrFormat("%ld ", ops_count);
      mac_str = absl::StrFormat("%ld ", ops_count / 2);
    } else if (ops_count < billion) {
      flops_str =
          absl::StrFormat("%.3f M ", static_cast<double>(ops_count) / million);
      mac_str = absl::StrFormat("%.3f M ",

}  // namespace
}  // namespace mlir

int main(int argc, char** argv) {
  llvm::InitLLVM y(argc, argv);
  llvm::cl::ParseCommandLineOptions(argc, argv);
  auto file_or_err = llvm::MemoryBuffer::getFileOrSTDIN(inputFileName.c_str());
  if (std::error_code error = file_or_err.getError()) {
    llvm::errs() << argv[0] << ": could not open input file '" << inputFileName
                 << "': " << error.message() << "\n";
    return 1;
  }

  std::string mat_mul_method =
      absl::StrFormat(kMatMulModuleStr, test_case.mat_mul_method);
  TF_ASSERT_OK_AND_ASSIGN(
      XlaCompiler::CompilationResult result,
      CompileMlirModule(
          mat_mul_method.c_str(),
          ConfigProto::Experimental::MLIR_BRIDGE_ROLLOUT_UNSPECIFIED));
}

INSTANTIATE_TEST_SUITE_P(
    BatchMatMulTest, BatchMatMulTest,
    ::testing::ValuesIn<MatMulTestCase>({
        {"BatchMatMul"},

  // delete[].  Returns the cloned string, or NULL if the input is
  // NULL.
  //
  // This is different from strdup() in string.h, which allocates
  // memory using malloc().
  static const char* CloneCString(const char* c_str);

#if GTEST_OS_WINDOWS_MOBILE
  // Windows CE does not have the 'ANSI' versions of Win32 APIs. To be
  // able to pass strings to Win32 APIs on CE we need to convert them
  // to 'Unicode', UTF-16.

        {
            "detail": [
                {
                    "loc": ["path", "item_id"],
                    "msg": "ensure this value has at least 3 characters",
                    "type": "value_error.any_str.min_length",
                    "ctx": {"limit_value": 3},
                }
            ]
        }
    )


def test_path_param_maxlength_foo():

        TFE_TensorHandleCopyToDevice(hcpu, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());
      continue;
    }
    // Copy from device to the same device.
    TFE_TensorHandle* hdevice2 =
        TFE_TensorHandleCopyToDevice(hdevice, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {

        | IsDict(
            {
                "ctx": {"limit_value": 1},
                "loc": ["query", "foo"],
                "msg": "ensure this value has at least 1 characters",
                "type": "value_error.any_str.min_length",
            }
        )
    ]
}


@pytest.mark.parametrize(
    "path,expected_status,expected_response",
    [
        ("/default", 200, {"foo": "foo"}),