






import argparse
import os
import re


__a:     List[Any]   					=					'''src/transformers/models/auto'''


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




def       _SCREAMING_SNAKE_CASE (							__snake_case   ,      __snake_case = False )				->						int:
       with open(__snake_case   ,      """r"""   ,      encoding="""utf-8""" ) as f:
              _UpperCAmelCase							=    f.read()

       _UpperCAmelCase							=    content.split("""\n""" )
       _UpperCAmelCase							=    []
       _UpperCAmelCase							=    0
       while line_idx < len(__snake_case ):
              if _re_intro_mapping.search(lines[line_idx] ) is not None:
                     _UpperCAmelCase							=    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

                     _UpperCAmelCase							=    []
                     while lines[line_idx].strip() != "]":
                            # Blocks either fit in one line or not
                            if lines[line_idx].strip() == "(":
                                   _UpperCAmelCase							=    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
                     _UpperCAmelCase							=    sorted(__snake_case   ,      key=lambda __snake_case : _re_identifier.search(__snake_case ).groups()[0] )
                     new_lines += blocks
              else:
                     new_lines.append(lines[line_idx] )
                     line_idx += 1

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




def       _SCREAMING_SNAKE_CASE (							__snake_case = False )				->						str:
       _UpperCAmelCase							=    [os.path.join(__snake_case   ,      __snake_case ) for f in os.listdir(__snake_case ) if f.endswith(""".py""" )]
       _UpperCAmelCase							=    [sort_auto_mapping(__snake_case   ,      overwrite=__snake_case ) for fname in fnames]

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


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

  sort_all_auto_mappings(not args.check_only)







from collections import OrderedDict
from typing import List, Mapping

from packaging import version

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


__a:     Dict   					=					logging.get_logger(__name__)

__a:     Optional[int]   					=					{
    '''google/efficientnet-b7''': '''https://huggingface.co/google/efficientnet-b7/resolve/main/config.json''',
}
class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  '''efficientnet'''


  def __init__(      self		:			Dict       ,				lowerCamelCase		:			int = 3       ,				lowerCamelCase		:			int = 600       ,				lowerCamelCase		:			float = 2.0       ,				lowerCamelCase		:			float = 3.1       ,				lowerCamelCase		:			int = 8       ,				lowerCamelCase		:			List[int] = [3, 3, 5, 3, 5, 5, 3]       ,				lowerCamelCase		:			List[int] = [32, 16, 24, 40, 80, 112, 192]       ,				lowerCamelCase		:			List[int] = [16, 24, 40, 80, 112, 192, 320]       ,				lowerCamelCase		:			List[int] = []       ,				lowerCamelCase		:			List[int] = [1, 2, 2, 2, 1, 2, 1]       ,				lowerCamelCase		:			List[int] = [1, 2, 2, 3, 3, 4, 1]       ,				lowerCamelCase		:			List[int] = [1, 6, 6, 6, 6, 6, 6]       ,				lowerCamelCase		:			float = 0.25       ,				lowerCamelCase		:			str = "swish"       ,				lowerCamelCase		:			int = 2560       ,				lowerCamelCase		:			str = "mean"       ,				lowerCamelCase		:			float = 0.02       ,				lowerCamelCase		:			float = 0.001       ,				lowerCamelCase		:			float = 0.99       ,				lowerCamelCase		:			float = 0.5       ,				lowerCamelCase		:			float = 0.2       ,				**lowerCamelCase		:			List[str]       ,				)						->	Union[str, Any]:


         """simple docstring"""
         super().__init__(**lowerCamelCase							)

         _UpperCAmelCase							=    num_channels
         _UpperCAmelCase							=    image_size
         _UpperCAmelCase							=    width_coefficient
         _UpperCAmelCase							=    depth_coefficient
         _UpperCAmelCase							=    depth_divisor
         _UpperCAmelCase							=    kernel_sizes
         _UpperCAmelCase							=    in_channels
         _UpperCAmelCase							=    out_channels
         _UpperCAmelCase							=    depthwise_padding
         _UpperCAmelCase							=    strides
         _UpperCAmelCase							=    num_block_repeats
         _UpperCAmelCase							=    expand_ratios
         _UpperCAmelCase							=    squeeze_expansion_ratio
         _UpperCAmelCase							=    hidden_act
         _UpperCAmelCase							=    hidden_dim
         _UpperCAmelCase							=    pooling_type
         _UpperCAmelCase							=    initializer_range
         _UpperCAmelCase							=    batch_norm_eps
         _UpperCAmelCase							=    batch_norm_momentum
         _UpperCAmelCase							=    dropout_rate
         _UpperCAmelCase							=    drop_connect_rate
         _UpperCAmelCase							=    sum(lowerCamelCase							) * 4



class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  version.parse('''1.11'''     )


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


         """simple docstring"""
         return OrderedDict(
             [
                 ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
             ]							)





  @property
  def  lowerCamelCase       (      self		:			Dict							)						->	float:


         """simple docstring"""
         return 1E-5