from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__magic_name__								=logging.get_logger(__name__)



class     _A   (    UpperCAmelCase_	, UpperCAmelCase_							):
  SCREAMING_SNAKE_CASE_	:	Dict						='maskformer-swin'

  SCREAMING_SNAKE_CASE_	:	Dict						={
      'num_attention_heads': 'num_heads',
      'num_hidden_layers': 'num_layers',
  }


  def __init__(self   ,				SCREAMING_SNAKE_CASE_=224   ,				SCREAMING_SNAKE_CASE_=4   ,				SCREAMING_SNAKE_CASE_=3   ,				SCREAMING_SNAKE_CASE_=96   ,				SCREAMING_SNAKE_CASE_=[2, 2, 6, 2]   ,				SCREAMING_SNAKE_CASE_=[3, 6, 12, 24]   ,				SCREAMING_SNAKE_CASE_=7   ,				SCREAMING_SNAKE_CASE_=4.0   ,				SCREAMING_SNAKE_CASE_=True   ,				SCREAMING_SNAKE_CASE_=0.0   ,				SCREAMING_SNAKE_CASE_=0.0   ,				SCREAMING_SNAKE_CASE_=0.1   ,				SCREAMING_SNAKE_CASE_="gelu"   ,				SCREAMING_SNAKE_CASE_=False   ,				SCREAMING_SNAKE_CASE_=0.02   ,				SCREAMING_SNAKE_CASE_=1E-5   ,				SCREAMING_SNAKE_CASE_=None   ,				SCREAMING_SNAKE_CASE_=None   ,				**SCREAMING_SNAKE_CASE_   ,				)		->      str:





       '''simple docstring'''





       super().__init__(**_lowercase	)

       UpperCamelCase__										=      image_size
       UpperCamelCase__										=      patch_size
       UpperCamelCase__										=      num_channels
       UpperCamelCase__										=      embed_dim
       UpperCamelCase__										=      depths
       UpperCamelCase__										=      len(_lowercase	)
       UpperCamelCase__										=      num_heads
       UpperCamelCase__										=      window_size
       UpperCamelCase__										=      mlp_ratio
       UpperCamelCase__										=      qkv_bias
       UpperCamelCase__										=      hidden_dropout_prob
       UpperCamelCase__										=      attention_probs_dropout_prob
       UpperCamelCase__										=      drop_path_rate
       UpperCamelCase__										=      hidden_act
       UpperCamelCase__										=      use_absolute_embeddings
       UpperCamelCase__										=      layer_norm_eps
       UpperCamelCase__										=      initializer_range
       # we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
       # this indicates the channel dimension after the last stage of the model
       UpperCamelCase__										=      int(embed_dim * 2 ** (len(_lowercase	) - 1)	)
       UpperCamelCase__										=      ['stem'] + [F"stage{idx}" for idx in range(1   ,				len(_lowercase	) + 1	)]
       UpperCamelCase__										=      get_aligned_output_features_output_indices(
           out_features=_lowercase   ,				out_indices=_lowercase   ,				stage_names=self.stage_names	)




from __future__ import annotations







def  __UpperCamelCase    (						A ,							A							):
     UpperCamelCase__										=      get_failure_array(A							)

     # 2) Step through text searching for pattern
     UpperCamelCase__						,       UpperCamelCase__										=      0, 0  # index into text, pattern
     while i < len(A							):
          if pattern[j] == text[i]:
               if j == (len(A							) - 1):
                    return True
               j += 1

          # if this is a prefix in our pattern
          # just go back far enough to continue
          elif j > 0:
               UpperCamelCase__										=      failure[j - 1]
               continue
          i += 1
     return False







def  __UpperCamelCase    (						A							):
     UpperCamelCase__										=      [0]
     UpperCamelCase__										=      0
     UpperCamelCase__										=      1
     while j < len(A							):
          if pattern[i] == pattern[j]:
               i += 1
          elif i > 0:
               UpperCamelCase__										=      failure[i - 1]
               continue
          j += 1
          failure.append(A							)
     return failure


if __name__ == "__main__":
     # Test 1)
     __magic_name__								='''abc1abc12'''
     __magic_name__								='''alskfjaldsabc1abc1abc12k23adsfabcabc'''
     __magic_name__								='''alskfjaldsk23adsfabcabc'''
     assert kmp(pattern, texta) and not kmp(pattern, texta)

     # Test 2)
     __magic_name__								='''ABABX'''
     __magic_name__								='''ABABZABABYABABX'''
     assert kmp(pattern, text)

     # Test 3)
     __magic_name__								='''AAAB'''
     __magic_name__								='''ABAAAAAB'''
     assert kmp(pattern, text)

     # Test 4)
     __magic_name__								='''abcdabcy'''
     __magic_name__								='''abcxabcdabxabcdabcdabcy'''
     assert kmp(pattern, text)

     # Test 5)
     __magic_name__								='''aabaabaaa'''
     assert get_failure_array(pattern) == [0, 1, 0, 1, 2, 3, 4, 5, 2]



