



'''simple docstring'''





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


lowercase_	 =						logging.get_logger(__name__)






class __A    (						A     ,     A		):



 '''simple docstring'''







 __lowerCamelCase					: int    = 'maskformer-swin'

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



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


      """simple docstring"""



      super().__init__(**A )

      _a											=						image_size
      _a											=						patch_size
      _a											=						num_channels
      _a											=						embed_dim
      _a											=						depths
      _a											=						len(A )
      _a											=						num_heads
      _a											=						window_size
      _a											=						mlp_ratio
      _a											=						qkv_bias
      _a											=						hidden_dropout_prob
      _a											=						attention_probs_dropout_prob
      _a											=						drop_path_rate
      _a											=						hidden_act
      _a											=						use_absolute_embeddings
      _a											=						layer_norm_eps
      _a											=						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
      _a											=						int(embed_dim * 2 ** (len(A ) - 1) )
      _a											=						['''stem'''] + [f'''stage{idx}''' for idx in range(1				,     len(A ) + 1 )]
      _a						,					_a											=						get_aligned_output_features_output_indices(
          out_features=A				,     out_indices=A				,     stage_names=self.stage_names )








'''simple docstring'''





lowercase_	 =						256
# Modulus to hash a string
lowercase_	 =						1_000_003




def lowerCAmelCase						(__A						,			__A):



     """simple docstring"""



     _a											=						len(__A)
     _a											=						len(__A)
     if p_len > t_len:
          return False

     _a											=						0
     _a											=						0
     _a											=						1

     # Calculating the hash of pattern and substring of text
     for i in range(__A):
          _a											=						(ord(pattern[i]) + p_hash * alphabet_size) % modulus
          _a											=						(ord(text[i]) + text_hash * alphabet_size) % modulus
          if i == p_len - 1:
               continue
          _a											=						(modulus_power * alphabet_size) % modulus

     for i in range(0						,			t_len - p_len + 1):
          if text_hash == p_hash and text[i : i + p_len] == pattern:
               return True
          if i == t_len - p_len:
               continue
          # Calculate the https://en.wikipedia.org/wiki/Rolling_hash
          _a											=						(
              (text_hash - ord(text[i]) * modulus_power) * alphabet_size
              + ord(text[i + p_len])
          ) % modulus
     return False




def lowerCAmelCase						():



     """simple docstring"""



     _a											=						'''abc1abc12'''
     _a											=						'''alskfjaldsabc1abc1abc12k23adsfabcabc'''
     _a											=						'''alskfjaldsk23adsfabcabc'''
     assert rabin_karp(__A						,			__A) and not rabin_karp(__A						,			__A)

     # Test 2)
     _a											=						'''ABABX'''
     _a											=						'''ABABZABABYABABX'''
     assert rabin_karp(__A						,			__A)

     # Test 3)
     _a											=						'''AAAB'''
     _a											=						'''ABAAAAAB'''
     assert rabin_karp(__A						,			__A)

     # Test 4)
     _a											=						'''abcdabcy'''
     _a											=						'''abcxabcdabxabcdabcdabcy'''
     assert rabin_karp(__A						,			__A)

     # Test 5)
     _a											=						'''Lü'''
     _a											=						'''Lüsai'''
     assert rabin_karp(__A						,			__A)
     _a											=						'''Lue'''
     assert not rabin_karp(__A						,			__A)
     print('''Success.''')


if __name__ == "__main__":
  test_rabin_karp()



