"""simple docstring"""



from typing import Optional, Union

from ...file_utils import TensorType
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, TruncationStrategy

class SCREAMING_SNAKE_CASE     (    a	):







 """simple docstring"""


 a_       :	List[str]  			="MarkupLMFeatureExtractor"
 a_       :	Union[str, Any]  			=("MarkupLMTokenizer", "MarkupLMTokenizerFast")
 a_       :	List[str]  			=True


 def __call__(   self		:      Union[str, Any]					,   _snake_case		:      Optional[int]=None					,   _snake_case		:      Any=None					,   _snake_case		:      int=None					,   _snake_case		:      Dict=None					,   _snake_case		:      Any=None					,   _snake_case		:      bool = True					,   _snake_case		:      Union[bool, str, PaddingStrategy] = False					,   _snake_case		:      Union[bool, str, TruncationStrategy] = None					,   _snake_case		:      Optional[int] = None					,   _snake_case		:      int = 0					,   _snake_case		:      Optional[int] = None					,   _snake_case		:      Optional[bool] = None					,   _snake_case		:      Optional[bool] = None					,   _snake_case		:      bool = False					,   _snake_case		:      bool = False					,   _snake_case		:      bool = False					,   _snake_case		:      bool = False					,   _snake_case		:      bool = True					,   _snake_case		:      Optional[Union[str, TensorType]] = None					,   **_snake_case		:      str					,   )				->			BatchEncoding:




    '''simple docstring'''






    if self.parse_html:
       if html_strings is None:
          raise ValueError('Make sure to pass HTML strings in case `parse_html` is set to `True`'				)

       if nodes is not None or xpaths is not None or node_labels is not None:
          raise ValueError(
              'Please don\'t pass nodes, xpaths nor node labels in case `parse_html` is set to `True`'				)

       a__     				=		self.feature_extractor(_snake_case				)
       a__     				=		features['nodes']
       a__     				=		features['xpaths']
    else:
       if html_strings is not None:
          raise ValueError('You have passed HTML strings but `parse_html` is set to `False`.'				)
       if nodes is None or xpaths is None:
          raise ValueError('Make sure to pass nodes and xpaths in case `parse_html` is set to `False`'				)

        # # second, apply the tokenizer
    if questions is not None and self.parse_html:
       if isinstance(_snake_case					,   _snake_case				):
          a__     				=		[questions]  # add batch dimension (as the feature extractor always adds a batch dimension)

    a__     				=		self.tokenizer(
        text=questions if questions is not None else nodes					,   text_pair=nodes if questions is not None else None					,   xpaths=_snake_case					,   node_labels=_snake_case					,   add_special_tokens=_snake_case					,   padding=_snake_case					,   truncation=_snake_case					,   max_length=_snake_case					,   stride=_snake_case					,   pad_to_multiple_of=_snake_case					,   return_token_type_ids=_snake_case					,   return_attention_mask=_snake_case					,   return_overflowing_tokens=_snake_case					,   return_special_tokens_mask=_snake_case					,   return_offsets_mapping=_snake_case					,   return_length=_snake_case					,   verbose=_snake_case					,   return_tensors=_snake_case					,   **_snake_case					,   )

    return encoded_inputs


 def        _lowerCAmelCase				(   self		:      str					,   *_snake_case		:      Optional[Any]					,   **_snake_case		:      Any				)				->			List[Any]:




    '''simple docstring'''






    return self.tokenizer.batch_decode(*_snake_case					,   **_snake_case				)


 def        _lowerCAmelCase				(   self		:      Optional[Any]					,   *_snake_case		:      Optional[int]					,   **_snake_case		:      str				)				->			Optional[int]:




    '''simple docstring'''






    return self.tokenizer.decode(*_snake_case					,   **_snake_case				)



 @property
 def        _lowerCAmelCase				(   self		:      Any				)				->			Union[str, Any]:




    '''simple docstring'''






    a__     				=		self.tokenizer.model_input_names
    return tokenizer_input_names



"""simple docstring"""



import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand





def   _lowerCamelCase ( UpperCAmelCase__					)							->     Any:


   '''simple docstring'''


   return EnvironmentCommand()




class SCREAMING_SNAKE_CASE     (    a	):







 """simple docstring"""


 @staticmethod
 def        _lowerCAmelCase				(   _snake_case		:      ArgumentParser				)				->			int:




    '''simple docstring'''






    a__     				=		parser.add_parser('env'					,   help='Print relevant system environment info.'				)
    download_parser.set_defaults(func=_snake_case				)


 def        _lowerCAmelCase				(   self		:      List[str]				)				->			Union[str, Any]:




    '''simple docstring'''






    a__     				=		{
        '`datasets` version': version,
        'Platform': platform.platform(),
        'Python version': platform.python_version(),
        'Huggingface_hub version': huggingface_hub.__version__,
        'PyArrow version': pyarrow.__version__,
        'Pandas version': pandas.__version__,
    }

    print('\nCopy-and-paste the text below in your GitHub issue.\n'				)
    print(self.format_dict(_snake_case				)				)

    return info



 @staticmethod
 def        _lowerCAmelCase				(   _snake_case		:      Tuple				)				->			Optional[int]:




    '''simple docstring'''






    return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]				) + "\n"


