"""simple docstring"""





import re
from pathlib import Path
from unittest import TestCase

import pytest
@pytest.mark.integration
class        _snake_case   (    snake_case_						):






						def 					lowerCamelCase__   (				self					:	Dict							,    UpperCAmelCase					:	Optional[int]			):




													with open(UpperCamelCase__							,    encoding="utf-8"			) as input_file:
																				__lowerCamelCase    :						int						      =   re.compile(r"(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)"			)
																				__lowerCamelCase    :						List[str]						      =   input_file.read()
																				__lowerCamelCase    :						List[Any]						      =   regexp.search(UpperCamelCase__			)

													return match






						def 					lowerCamelCase__   (				self					:	List[str]							,    UpperCAmelCase					:	Dict			):




													with open(UpperCamelCase__							,    encoding="utf-8"			) as input_file:
																				__lowerCamelCase    :						Optional[int]						      =   re.compile(r"#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()"							,    re.DOTALL			)
																				__lowerCamelCase    :						Dict						      =   input_file.read()
																				# use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
																				__lowerCamelCase    :						str						      =   regexp.finditer(UpperCamelCase__			)

													__lowerCamelCase    :						Optional[Any]						      =   [match for match in matches if match is not None and match.group(1			) is not None]
													return matches[0] if matches else None






						def 					lowerCamelCase__   (				self					:	int			):
													__lowerCamelCase    :						int						      =   Path("./datasets"			)
													__lowerCamelCase    :						Optional[int]						      =   list(dataset_paths.absolute().glob("**/*.py"			)			)

													for dataset in dataset_files:
																				if self._no_encoding_on_file_open(str(UpperCamelCase__			)			):
																											raise AssertionError(F"""open(...) must use utf-8 encoding in {dataset}"""			)







						def 					lowerCamelCase__   (				self					:	int			):
													__lowerCamelCase    :						Any						      =   Path("./datasets"			)
													__lowerCamelCase    :						Any						      =   list(dataset_paths.absolute().glob("**/*.py"			)			)

													for dataset in dataset_files:
																				if self._no_print_statements(str(UpperCamelCase__			)			):
																											raise AssertionError(F"""print statement found in {dataset}. Use datasets.logger/logging instead."""			)



"""simple docstring"""



from typing import Dict

from .base import GenericTensor, Pipeline







class _lowerCAmelCase				(      snake_case_	):







   def  lowerCamelCase		(	self						,	UpperCamelCase__=None						,	UpperCamelCase__=None						,	UpperCamelCase__=None						,	**UpperCamelCase__						)	->		Union[str, Any]:

       '''simple docstring'''




       if tokenize_kwargs is None:
           snake_case    :      Optional[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)"						)
           snake_case    :      List[str]      					=    truncation

       snake_case    :      Union[str, Any]      					=    tokenize_kwargs

       snake_case    :      List[Any]      					=    {}
       if return_tensors is not None:
           snake_case    :      Tuple      					=    return_tensors

       return preprocess_params, {}, postprocess_params







   def  lowerCamelCase		(	self						,	UpperCamelCase__						,	**UpperCamelCase__						)	->		Dict[str, GenericTensor]:

       '''simple docstring'''




       snake_case    :      List[Any]      					=    self.framework
       snake_case    :      str      					=    self.tokenizer(UpperCamelCase__						,	return_tensors=UpperCamelCase__						,	**UpperCamelCase__						)
       return model_inputs







   def  lowerCamelCase		(	self						,	UpperCamelCase__						)	->		Tuple:

       '''simple docstring'''




       snake_case    :      int      					=    self.model(**UpperCamelCase__						)
       return model_outputs







   def  lowerCamelCase		(	self						,	UpperCamelCase__						,	UpperCamelCase__=False						)	->		Union[str, Any]:

       '''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						,	*UpperCamelCase__						,	**UpperCamelCase__						)	->		Union[str, Any]:

       '''simple docstring'''




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





