self = <test.integ_test.evaluator.local_eval.test_local_evaluation.TestLocalEvaluation object at 0x7f9db6f98df0>
type = 'HfModel'
model_config_func = <function get_huggingface_model at 0x7f9db6f7bf40>
metric_func = <function get_hf_accuracy_metric at 0x7f9db6f7bd90>
expected_res = 0.1

    @pytest.mark.parametrize(
        ("type", "model_config_func", "metric_func", "expected_res"),
        EVALUATION_TEST_CASE,
    )
    def test_evaluate_model(self, type, model_config_func, metric_func, expected_res):  # noqa: A002
        model_config = model_config_func()
        metric = metric_func()
        model_config = ModelConfig.parse_obj({"type": type, "config": model_config})
        evaluator_config = OliveEvaluatorConfig(metrics=[metric])
>       actual_res = LocalSystem().evaluate_model(model_config, evaluator_config, DEFAULT_CPU_ACCELERATOR)

test/integ_test/evaluator/local_eval/test_local_evaluation.py:63: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
olive/systems/local.py:44: in evaluate_model
    return evaluator.evaluate(
olive/evaluator/olive_evaluator.py:315: in evaluate
    dataloader, eval_func, post_func = OliveEvaluator.get_user_config(model.framework, metric)
olive/evaluator/olive_evaluator.py:136: in get_user_config
    dataloader = dc.create_dataloader()
olive/data/container/data_container.py:45: in create_dataloader
    dataset = self.load_dataset()
olive/data/container/data_container.py:26: in load_dataset
    return self.config.load_dataset(**self.config.load_dataset_params)
test/integ_test/evaluator/local_eval/user_script.py:46: in tiny_bert_dataset_for_local_eval
    dataset = load_dataset("glue", "mrpc", split="validation")
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:2556: in load_dataset
    builder_instance = load_dataset_builder(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:2228: in load_dataset_builder
    dataset_module = dataset_module_factory(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:1879: in dataset_module_factory
    raise e1 from None
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:1861: in dataset_module_factory
    ).get_module()
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:1239: in get_module
    data_files = DataFilesDict.from_patterns(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/data_files.py:700: in from_patterns
    DataFilesList.from_patterns(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/data_files.py:605: in from_patterns
    resolve_pattern(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/data_files.py:354: in resolve_pattern
    fs, _, _ = get_fs_token_paths(pattern, storage_options=storage_options)
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/fsspec/core.py:640: in get_fs_token_paths
    paths = [f for f in sorted(fs.glob(paths)) if not fs.isdir(f)]
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/huggingface_hub/hf_file_system.py:521: in glob
    return super().glob(path, **kwargs)
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/fsspec/spec.py:602: in glob
    allpaths = self.find(root, maxdepth=depth, withdirs=True, detail=True, **kwargs)
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/huggingface_hub/hf_file_system.py:556: in find
    return super().find(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/fsspec/spec.py:493: in find
    out[path] = self.info(path)
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/huggingface_hub/hf_file_system.py:719: in info
    paths_info = self._api.get_paths_info(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114: in _inner_fn
   

self = <test.integ_test.evaluator.local_eval.test_local_evaluation.TestLocalEvaluation object at 0x7f9db6f98d30>
type = 'HfModel'
model_config_func = <function get_huggingface_model at 0x7f9db6f7bf40>
metric_func = <function get_hf_latency_metric at 0x7f9db6f7be20>
expected_res = 0.001

    @pytest.mark.parametrize(
        ("type", "model_config_func", "metric_func", "expected_res"),
        EVALUATION_TEST_CASE,
    )
    def test_evaluate_model(self, type, model_config_func, metric_func, expected_res):  # noqa: A002
        model_config = model_config_func()
        metric = metric_func()
        model_config = ModelConfig.parse_obj({"type": type, "config": model_config})
        evaluator_config = OliveEvaluatorConfig(metrics=[metric])
>       actual_res = LocalSystem().evaluate_model(model_config, evaluator_config, DEFAULT_CPU_ACCELERATOR)

test/integ_test/evaluator/local_eval/test_local_evaluation.py:63: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
olive/systems/local.py:44: in evaluate_model
    return evaluator.evaluate(
olive/evaluator/olive_evaluator.py:315: in evaluate
    dataloader, eval_func, post_func = OliveEvaluator.get_user_config(model.framework, metric)
olive/evaluator/olive_evaluator.py:136: in get_user_config
    dataloader = dc.create_dataloader()
olive/data/container/data_container.py:45: in create_dataloader
    dataset = self.load_dataset()
olive/data/container/data_container.py:26: in load_dataset
    return self.config.load_dataset(**self.config.load_dataset_params)
test/integ_test/evaluator/local_eval/user_script.py:46: in tiny_bert_dataset_for_local_eval
    dataset = load_dataset("glue", "mrpc", split="validation")
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:2556: in load_dataset
    builder_instance = load_dataset_builder(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:2228: in load_dataset_builder
    dataset_module = dataset_module_factory(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:1879: in dataset_module_factory
    raise e1 from None
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:1861: in dataset_module_factory
    ).get_module()
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/datasets/load.py:1191: in get_module
    hfh_dataset_info = HfApi(config.HF_ENDPOINT).dataset_info(
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114: in _inner_fn
    return fn(*args, **kwargs)
/opt/hostedtoolcache/Python/3.10.16/x64/lib/python3.10/site-packages/huggingface_hub/hf_api.py:2592: in dataset_info
    hf_raise_for_status(r)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

response = <Response [504]>, endpoint_name = None

    def hf_raise_for_status(response: Response, endpoint_name: Optional[str] = None) -> None:
        """
        Internal version of `response.raise_for_status()` that will refine a
        potential HTTPError. Raised exception will be an instance of `HfHubHTTPError`.
    
        This helper is meant to be the unique method to raise_for_status when making a call
        to the Hugging Face Hub.
    
    
        Example:
        ```py
            import requests
            from huggingface_hub.utils import get_session, hf_raise_for_status, HfHubHTTPError
    
            response = get_session().post(...)
            try:
                hf_raise_for_status(response)
            except HfHubHTTPError as e:
                print(str(e)) # formatted message
                e.request_id, e.server_message # details returned by server
    
                # Complete the error message with additional information once it's raised
                e.append_to_message("\n`create_commit` expects the repository to exist.")
                raise
        ```
    
        Args:
            r