


import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline



@pytest.mark.integration
def        UpperCamelCase_(   )					->		List[str]:

    with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT				):
        with pytest.raises(SCREAMING_SNAKE_CASE_				):
            requests.request('GET'							,				'https://huggingface.co'				)
        with pytest.raises(requests.exceptions.ConnectTimeout				):
            requests.request('GET'							,				'https://huggingface.co'							,				timeout=1.0				)



@pytest.mark.integration
def        UpperCamelCase_(   )					->		Dict:

    with offline(OfflineSimulationMode.CONNECTION_FAILS				):
        with pytest.raises(requests.exceptions.ConnectionError				):
            requests.request('GET'							,				'https://huggingface.co'				)



def        UpperCamelCase_(   )					->		Any:

    with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1				):
        with pytest.raises(SCREAMING_SNAKE_CASE_				):
            http_head('https://huggingface.co'				)






from typing import Dict

from .base import GenericTensor, Pipeline






class _lowerCamelCase(		_a     ):
       def     UpperCamelCase  (      self,   lowerCamelCase=None,   lowerCamelCase=None,   lowerCamelCase=None,   **lowerCamelCase) ->     int:




           """simple docstring"""

           if tokenize_kwargs is None:
               _lowercase :							Any   	=	{}

           if truncation is not None:
               if "truncation" in tokenize_kwargs:
                   raise ValueError(
                       'truncation parameter defined twice (given as keyword argument as well as in tokenize_kwargs)')
               _lowercase :							List[Any]   	=	truncation

           _lowercase :							Optional[Any]   	=	tokenize_kwargs

           _lowercase :							Tuple   	=	{}
           if return_tensors is not None:
               _lowercase :							Union[str, Any]   	=	return_tensors

           return preprocess_params, {}, postprocess_params
       def     UpperCamelCase  (      self,   lowerCamelCase,   **lowerCamelCase) ->     Dict[str, GenericTensor]:




           """simple docstring"""

           _lowercase :							Optional[Any]   	=	self.framework
           _lowercase :							Dict   	=	self.tokenizer(lowerCamelCase,   return_tensors=lowerCamelCase,   **lowerCamelCase)
           return model_inputs
       def     UpperCamelCase  (      self,   lowerCamelCase) ->     Optional[Any]:




           """simple docstring"""

           _lowercase :							str   	=	self.model(**lowerCamelCase)
           return model_outputs
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase=False) ->     Dict:




           """simple docstring"""

           if return_tensors:
               return model_outputs[0]
           if self.framework == "pt":
               return model_outputs[0].tolist()
           elif self.framework == "tf":
               return model_outputs[0].numpy().tolist()




       def __call__(      self,   *lowerCamelCase,   **lowerCamelCase) ->     Union[str, Any]:




           """simple docstring"""

           return super().__call__(*lowerCamelCase,   **lowerCamelCase)


