

'''simple docstring'''

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_       						=							logging.get_logger(__name__)

A_       						=							{
    "google/efficientnet-b7": "https://huggingface.co/google/efficientnet-b7/resolve/main/config.json",
}





class 							_snake_case (       _a						):
   _A       :     Dict       =					'''efficientnet'''
   def __init__( self			:      Optional[int]     ,SCREAMING_SNAKE_CASE__			:      int = 3     ,SCREAMING_SNAKE_CASE__			:      int = 600     ,SCREAMING_SNAKE_CASE__			:      float = 2.0     ,SCREAMING_SNAKE_CASE__			:      float = 3.1     ,SCREAMING_SNAKE_CASE__			:      int = 8     ,SCREAMING_SNAKE_CASE__			:      List[int] = [3, 3, 5, 3, 5, 5, 3]     ,SCREAMING_SNAKE_CASE__			:      List[int] = [32, 16, 24, 40, 80, 112, 192]     ,SCREAMING_SNAKE_CASE__			:      List[int] = [16, 24, 40, 80, 112, 192, 320]     ,SCREAMING_SNAKE_CASE__			:      List[int] = []     ,SCREAMING_SNAKE_CASE__			:      List[int] = [1, 2, 2, 2, 1, 2, 1]     ,SCREAMING_SNAKE_CASE__			:      List[int] = [1, 2, 2, 3, 3, 4, 1]     ,SCREAMING_SNAKE_CASE__			:      List[int] = [1, 6, 6, 6, 6, 6, 6]     ,SCREAMING_SNAKE_CASE__			:      float = 0.25     ,SCREAMING_SNAKE_CASE__			:      str = "swish"     ,SCREAMING_SNAKE_CASE__			:      int = 2_560     ,SCREAMING_SNAKE_CASE__			:      str = "mean"     ,SCREAMING_SNAKE_CASE__			:      float = 0.02     ,SCREAMING_SNAKE_CASE__			:      float = 0.001     ,SCREAMING_SNAKE_CASE__			:      float = 0.99     ,SCREAMING_SNAKE_CASE__			:      float = 0.5     ,SCREAMING_SNAKE_CASE__			:      float = 0.2     ,**SCREAMING_SNAKE_CASE__			:      str     ,):
     super().__init__(**SCREAMING_SNAKE_CASE__							)

     SCREAMING_SNAKE_CASE:List[Any]						      =					num_channels
     SCREAMING_SNAKE_CASE:int						      =					image_size
     SCREAMING_SNAKE_CASE:Tuple						      =					width_coefficient
     SCREAMING_SNAKE_CASE:str						      =					depth_coefficient
     SCREAMING_SNAKE_CASE:Optional[int]						      =					depth_divisor
     SCREAMING_SNAKE_CASE:Optional[int]						      =					kernel_sizes
     SCREAMING_SNAKE_CASE:Tuple						      =					in_channels
     SCREAMING_SNAKE_CASE:str						      =					out_channels
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					depthwise_padding
     SCREAMING_SNAKE_CASE:str						      =					strides
     SCREAMING_SNAKE_CASE:List[Any]						      =					num_block_repeats
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					expand_ratios
     SCREAMING_SNAKE_CASE:str						      =					squeeze_expansion_ratio
     SCREAMING_SNAKE_CASE:Optional[Any]						      =					hidden_act
     SCREAMING_SNAKE_CASE:Dict						      =					hidden_dim
     SCREAMING_SNAKE_CASE:Tuple						      =					pooling_type
     SCREAMING_SNAKE_CASE:List[Any]						      =					initializer_range
     SCREAMING_SNAKE_CASE:Tuple						      =					batch_norm_eps
     SCREAMING_SNAKE_CASE:str						      =					batch_norm_momentum
     SCREAMING_SNAKE_CASE:int						      =					dropout_rate
     SCREAMING_SNAKE_CASE:str						      =					drop_connect_rate
     SCREAMING_SNAKE_CASE:int						      =					sum(SCREAMING_SNAKE_CASE__							) * 4





class 							_snake_case (       _a						):
   _A       :     Optional[Any]       =					version.parse('''1.11'''						)
   @property
   def     __UpperCamelCase						( self			:      Union[str, Any]							):
     return OrderedDict(
         [
             ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
         ]							)







   @property
   def     __UpperCamelCase						( self			:      Dict							):
     return 1e-5









'''simple docstring'''

def    A_  ( snake_case      ,       snake_case ):
  SCREAMING_SNAKE_CASE:Optional[int]						      =					word.split()

  def justify(snake_case      ,       snake_case      ,       snake_case ) -> str:
    SCREAMING_SNAKE_CASE:str						      =					max_width - width
    SCREAMING_SNAKE_CASE:Dict						      =					len(snake_case )
    if len(snake_case ) == 1:
      # if there is only word in line
      # just insert overall_spaces_count for the remainder of line
      return line[0] + " " * overall_spaces_count
    else:
      SCREAMING_SNAKE_CASE:Optional[int]						      =					words_count - 1
      # num_spaces_between_words_list[i] : tells you to insert
      # num_spaces_between_words_list[i] spaces
      # after word on line[i]
      SCREAMING_SNAKE_CASE:List[Any]						      =					spaces_to_insert_between_words * [
          overall_spaces_count // spaces_to_insert_between_words
      ]
      SCREAMING_SNAKE_CASE:List[Any]						      =					(
          overall_spaces_count % spaces_to_insert_between_words
      )
      # distribute spaces via round robin to the left words
      for i in range(snake_case ):
        num_spaces_between_words_list[i] += 1
      SCREAMING_SNAKE_CASE:str						      =					[]
      for i in range(snake_case ):
        # add the word
        aligned_words_list.append(line[i] )
        # add the spaces to insert
        aligned_words_list.append(num_spaces_between_words_list[i] * " " )
      # just add the last word to the sentence
      aligned_words_list.append(line[-1] )
      # join the aligned words list to form a justified line
      return "".join(snake_case )

  SCREAMING_SNAKE_CASE:Any						      =					[]
  SCREAMING_SNAKE_CASE:list[str]						      =					[]
  SCREAMING_SNAKE_CASE:List[str]						      =					0
  for word in words:
    if width + len(snake_case ) + len(snake_case ) <= max_width:
      # keep adding words until we can fill out max_width
      # width = sum of length of all words (without overall_spaces_count)
      # len(word) = length of current word
      # len(line) = number of overall_spaces_count to insert between words
      line.append(snake_case )
      width += len(snake_case )
    else:
      # justify the line and add it to result
      answer.append(justify(snake_case      ,       snake_case      ,       snake_case ) )
      # reset new line and new width
      SCREAMING_SNAKE_CASE      ,    SCREAMING_SNAKE_CASE:Tuple						      =					[word], len(snake_case )
  SCREAMING_SNAKE_CASE:Optional[int]						      =					max_width - width - len(snake_case )
  answer.append(" ".join(snake_case ) + (remaining_spaces + 1) * " " )
  return answer


if __name__ == "__main__":
    from doctest import testmod

    testmod()






