




import argparse
import os
import re


lowerCAmelCase_						=			'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
lowerCAmelCase_						=			re.compile(R'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
lowerCAmelCase_						=			re.compile(R'\s*\(\s*"(\S[^"]+)"')






def  snake_case(    __magic_name__			,		__magic_name__ = False   )			->							int:





     '''simple docstring'''


     with open(__magic_name__			,		'''r'''			,		encoding='''utf-8'''   ) as f:
          lowercase :       int       =			f.read()

     lowercase :       str       =			content.split('''\n'''   )
     lowercase :       List[str]       =			[]
     lowercase :       Optional[Any]       =			0
     while line_idx < len(__magic_name__   ):
          if _re_intro_mapping.search(lines[line_idx]   ) is not None:
               lowercase :       Union[str, Any]       =			len(re.search(r'''^(\s*)\S'''			,		lines[line_idx]   ).groups()[0]   ) + 8
               # Start of a new mapping!
               while not lines[line_idx].startswith(''' ''' * indent + '''('''   ):
                    new_lines.append(lines[line_idx]   )
                    line_idx += 1

               lowercase :       Union[str, Any]       =			[]
               while lines[line_idx].strip() != "]":
                    # Blocks either fit in one line or not
                    if lines[line_idx].strip() == "(":
                         lowercase :       int       =			line_idx
                         while not lines[line_idx].startswith(''' ''' * indent + ''')'''   ):
                              line_idx += 1
                         blocks.append('''\n'''.join(lines[start_idx : line_idx + 1]   )   )
                    else:
                         blocks.append(lines[line_idx]   )
                    line_idx += 1

               # Sort blocks by their identifiers
               lowercase :       List[Any]       =			sorted(__magic_name__			,		key=lambda __magic_name__   : _re_identifier.search(__magic_name__   ).groups()[0]   )
               new_lines += blocks
          else:
               new_lines.append(lines[line_idx]   )
               line_idx += 1

     if overwrite:
          with open(__magic_name__			,		'''w'''			,		encoding='''utf-8'''   ) as f:
               f.write('''\n'''.join(__magic_name__   )   )
     elif "\n".join(__magic_name__   ) != content:
          return True






def  snake_case(    __magic_name__ = False   )			->							Tuple:





     '''simple docstring'''


     lowercase :       Optional[int]       =			[os.path.join(__magic_name__			,		__magic_name__   ) for f in os.listdir(__magic_name__   ) if f.endswith('''.py'''   )]
     lowercase :       List[Any]       =			[sort_auto_mapping(__magic_name__			,		overwrite=__magic_name__   ) for fname in fnames]

     if not overwrite and any(__magic_name__   ):
          lowercase :       str       =			[f for f, d in zip(__magic_name__			,		__magic_name__   ) if d]
          raise ValueError(
              F"""The following files have auto mappings that need sorting: {', '.join(__magic_name__   )}. Run `make style` to fix"""
              ''' this.'''   )


if __name__ == "__main__":
 lowerCAmelCase_						=			argparse.ArgumentParser()
 parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
 lowerCAmelCase_						=			parser.parse_args()

 sort_all_auto_mappings(not args.check_only)





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCAmelCase_						=			logging.get_logger(__name__)

lowerCAmelCase_						=			{
    'facebook/xmod-base': 'https://huggingface.co/facebook/xmod-base/resolve/main/config.json',
    'facebook/xmod-large-prenorm': 'https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json',
    'facebook/xmod-base-13-125k': 'https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json',
    'facebook/xmod-base-30-125k': 'https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json',
    'facebook/xmod-base-30-195k': 'https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json',
    'facebook/xmod-base-60-125k': 'https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json',
    'facebook/xmod-base-60-265k': 'https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json',
    'facebook/xmod-base-75-125k': 'https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json',
    'facebook/xmod-base-75-269k': 'https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json',
}
class 						_A (  _lowerCamelCase				):
  _UpperCamelCase       :      Tuple			=      '''xmod'''






  def __init__(  self		:     Optional[Any]				,						_A		:     Union[str, Any]=30_522				,						_A		:     List[Any]=768				,						_A		:     Optional[Any]=12				,						_A		:     Any=12				,						_A		:     Tuple=3_072				,						_A		:     Optional[int]="gelu"				,						_A		:     List[Any]=0.1				,						_A		:     str=0.1				,						_A		:     List[Any]=512				,						_A		:     List[str]=2				,						_A		:     str=0.02				,						_A		:     Any=1E-12				,						_A		:     Union[str, Any]=1				,						_A		:     List[Any]=0				,						_A		:     Dict=2				,						_A		:     int="absolute"				,						_A		:     Dict=True				,						_A		:     int=None				,						_A		:     List[str]=False				,						_A		:     Dict=2				,						_A		:     int=False				,						_A		:     Optional[int]=True				,						_A		:     Any=True				,						_A		:     Optional[int]=("en_XX",)				,						_A		:     Any=None				,						**_A		:     Optional[int]				,						)		->   Union[str, Any]:






       """simple docstring"""







       super().__init__(pad_token_id=_A				,						bos_token_id=_A				,						eos_token_id=_A				,						**_A				)

       lowercase :       Optional[Any]       =			vocab_size
       lowercase :       Union[str, Any]       =			hidden_size
       lowercase :       Optional[Any]       =			num_hidden_layers
       lowercase :       Dict       =			num_attention_heads
       lowercase :       Union[str, Any]       =			hidden_act
       lowercase :       Tuple       =			intermediate_size
       lowercase :       List[str]       =			hidden_dropout_prob
       lowercase :       Union[str, Any]       =			attention_probs_dropout_prob
       lowercase :       Dict       =			max_position_embeddings
       lowercase :       Any       =			type_vocab_size
       lowercase :       Optional[Any]       =			initializer_range
       lowercase :       str       =			layer_norm_eps
       lowercase :       Tuple       =			position_embedding_type
       lowercase :       Optional[Any]       =			use_cache
       lowercase :       int       =			classifier_dropout
       lowercase :       Optional[int]       =			pre_norm
       lowercase :       Any       =			adapter_reduction_factor
       lowercase :       Union[str, Any]       =			adapter_layer_norm
       lowercase :       Optional[int]       =			adapter_reuse_layer_norm
       lowercase :       Optional[Any]       =			ln_before_adapter
       lowercase :       Union[str, Any]       =			list(_A				)
       lowercase :       List[Any]       =			default_language


class 						_A (  _lowerCamelCase				):






  @property
  def  __a      (  self		:     Union[str, Any]				)		->   Mapping[str, Mapping[int, str]]:






       """simple docstring"""







       if self.task == "multiple-choice":
            lowercase :       Any       =			{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
       else:
            lowercase :       Union[str, Any]       =			{0: '''batch''', 1: '''sequence'''}
       return OrderedDict(
           [
               ('''input_ids''', dynamic_axis),
               ('''attention_mask''', dynamic_axis),
           ]				)