


from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase		   =			logging.get_logger(__name__)

lowerCamelCase		   =			{
    'microsoft/swinv2-tiny-patch4-window8-256': (
        'https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'
    ),
}




class A    (  UpperCamelCase_	):
      UpperCamelCase__				:    Tuple ='swinv2'

      UpperCamelCase__				:    str ={
          'num_attention_heads': 'num_heads',
          'num_hidden_layers': 'num_layers',
      }






      def __init__(   self		:	Optional[int]     ,  lowercase_		:	int=224     ,  lowercase_		:	Optional[int]=4     ,  lowercase_		:	Union[str, Any]=3     ,  lowercase_		:	Union[str, Any]=96     ,  lowercase_		:	str=[2, 2, 6, 2]     ,  lowercase_		:	Optional[int]=[3, 6, 12, 24]     ,  lowercase_		:	Optional[Any]=7     ,  lowercase_		:	Optional[int]=4.0     ,  lowercase_		:	Tuple=True     ,  lowercase_		:	Optional[int]=0.0     ,  lowercase_		:	List[Any]=0.0     ,  lowercase_		:	Dict=0.1     ,  lowercase_		:	Optional[int]="gelu"     ,  lowercase_		:	int=False     ,  lowercase_		:	int=0.02     ,  lowercase_		:	str=1E-5     ,  lowercase_		:	Any=32     ,  **lowercase_		:	List[str]     ,  )   ->		Optional[int]:
             """simple docstring"""




             super().__init__(**lowercase_					)

             _lowerCamelCase			:						Dict            =image_size
             _lowerCamelCase			:						Tuple            =patch_size
             _lowerCamelCase			:						List[Any]            =num_channels
             _lowerCamelCase			:						Optional[Any]            =embed_dim
             _lowerCamelCase			:						str            =depths
             _lowerCamelCase			:						List[Any]            =len(lowercase_					)
             _lowerCamelCase			:						str            =num_heads
             _lowerCamelCase			:						List[Any]            =window_size
             _lowerCamelCase			:						Union[str, Any]            =mlp_ratio
             _lowerCamelCase			:						Union[str, Any]            =qkv_bias
             _lowerCamelCase			:						Tuple            =hidden_dropout_prob
             _lowerCamelCase			:						str            =attention_probs_dropout_prob
             _lowerCamelCase			:						List[Any]            =drop_path_rate
             _lowerCamelCase			:						Any            =hidden_act
             _lowerCamelCase			:						str            =use_absolute_embeddings
             _lowerCamelCase			:						List[Any]            =layer_norm_eps
             _lowerCamelCase			:						Optional[int]            =initializer_range
             _lowerCamelCase			:						Optional[int]            =encoder_stride
             # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
             # this indicates the channel dimension after the last stage of the model
             _lowerCamelCase			:						Any            =int(embed_dim * 2 ** (len(lowercase_					) - 1)					)
             _lowerCamelCase			:						Optional[Any]            =(0, 0, 0, 0)






from timeit import timeit

lowerCamelCase		   =			{
    'MALAYALAM': True,
    'String': False,
    'rotor': True,
    'level': True,
    'A': True,
    'BB': True,
    'ABC': False,
    'amanaplanacanalpanama': True,  # "a man a plan a canal panama"
}
# Ensure our test data is valid
assert all((key == key[::-1]) is value for key, value in test_data.items())




def       a_ (       SCREAMING_SNAKE_CASE__   : str	):
       '''simple docstring'''





       _lowerCamelCase			:						Optional[int]            =0
       _lowerCamelCase			:						Union[str, Any]            =len(SCREAMING_SNAKE_CASE__	) - 1
       while start_i < end_i:
              if s[start_i] == s[end_i]:
                     start_i += 1
                     end_i -= 1
              else:
                     return False
       return True




def       a_ (       SCREAMING_SNAKE_CASE__   : str	):
       '''simple docstring'''





       _lowerCamelCase			:						List[str]            =len(SCREAMING_SNAKE_CASE__	) // 2
       _lowerCamelCase			:						Optional[Any]            =len(SCREAMING_SNAKE_CASE__	)

       # We need to traverse till half of the length of string
       # as we can get access of the i'th last element from
       # i'th index.
       # eg: [0,1,2,3,4,5] => 4th index can be accessed
       # with the help of 1st index (i==n-i-1)
       # where n is length of string
       return all(s[i] == s[n - i - 1] for i in range(SCREAMING_SNAKE_CASE__	)	)




def       a_ (       SCREAMING_SNAKE_CASE__   : str	):
       '''simple docstring'''





       if len(SCREAMING_SNAKE_CASE__	) <= 2:
              return True
       if s[0] == s[len(SCREAMING_SNAKE_CASE__	) - 1]:
              return is_palindrome_recursive(s[1:-1]	)
       else:
              return False




def       a_ (       SCREAMING_SNAKE_CASE__   : str	):
       '''simple docstring'''





       return s == s[::-1]




def       a_ (       SCREAMING_SNAKE_CASE__   : str	):
       '''simple docstring'''





       _lowerCamelCase			:						Optional[int]            =F'''all({name}(key) is value for key, value in test_data.items())'''
       _lowerCamelCase			:						List[Any]            =F'''from __main__ import test_data, {name}'''
       _lowerCamelCase			:						Any            =500_000
       _lowerCamelCase			:						Dict            =timeit(stmt=SCREAMING_SNAKE_CASE__						,     setup=SCREAMING_SNAKE_CASE__						,     number=SCREAMING_SNAKE_CASE__	)
       print(F'''{name:<35} finished {number:,} runs in {result:.5f} seconds'''	)


if __name__ == "__main__":
 for key, value in test_data.items():
  assert is_palindrome(key) is is_palindrome_recursive(key)
  assert is_palindrome(key) is is_palindrome_slice(key)
  print(F"""{key:21} {value}""")
 print('a man a plan a canal panama')

 # finished 500,000 runs in 0.46793 seconds
 benchmark_function('is_palindrome_slice')
 # finished 500,000 runs in 0.85234 seconds
 benchmark_function('is_palindrome')
 # finished 500,000 runs in 1.32028 seconds
 benchmark_function('is_palindrome_recursive')
 # finished 500,000 runs in 2.08679 seconds
 benchmark_function('is_palindrome_traversal')


