






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


__UpperCAmelCase								=						logging.get_logger(__name__)

__UpperCAmelCase								=						{
    'shi-labs/dinat-mini-in1k-224': 'https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json',
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}



class   lowerCamelCase      (_SCREAMING_SNAKE_CASE ,  _SCREAMING_SNAKE_CASE			):







		'''simple docstring'''



		_snake_case    :    Optional[int]       						=  '''dinat'''

		_snake_case    :    Union[str, Any]       						=  {
		    '''num_attention_heads''': '''num_heads''',
		    '''num_hidden_layers''': '''num_layers''',
		}



		def __init__(							self				,		_UpperCamelCase=4				,		_UpperCamelCase=3				,		_UpperCamelCase=6_4				,		_UpperCamelCase=[3, 4, 6, 5]				,		_UpperCamelCase=[2, 4, 8, 1_6]				,		_UpperCamelCase=7				,		_UpperCamelCase=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]				,		_UpperCamelCase=3.0				,		_UpperCamelCase=True				,		_UpperCamelCase=0.0				,		_UpperCamelCase=0.0				,		_UpperCamelCase=0.1				,		_UpperCamelCase="gelu"				,		_UpperCamelCase=0.02				,		_UpperCamelCase=1E-5				,		_UpperCamelCase=0.0				,		_UpperCamelCase=None				,		_UpperCamelCase=None				,		**_UpperCamelCase				,		)	->							Dict:
							super().__init__(**_lowerCAmelCase   )

							UpperCAmelCase_    :      Any            =						patch_size
							UpperCAmelCase_    :      List[Any]            =						num_channels
							UpperCAmelCase_    :      Optional[int]            =						embed_dim
							UpperCAmelCase_    :      Optional[int]            =						depths
							UpperCAmelCase_    :      List[Any]            =						len(_lowerCAmelCase   )
							UpperCAmelCase_    :      List[Any]            =						num_heads
							UpperCAmelCase_    :      List[str]            =						kernel_size
							UpperCAmelCase_    :      Union[str, Any]            =						dilations
							UpperCAmelCase_    :      List[str]            =						mlp_ratio
							UpperCAmelCase_    :      Tuple            =						qkv_bias
							UpperCAmelCase_    :      Optional[Any]            =						hidden_dropout_prob
							UpperCAmelCase_    :      int            =						attention_probs_dropout_prob
							UpperCAmelCase_    :      List[Any]            =						drop_path_rate
							UpperCAmelCase_    :      Optional[int]            =						hidden_act
							UpperCAmelCase_    :      Any            =						layer_norm_eps
							UpperCAmelCase_    :      Optional[Any]            =						initializer_range
							# we set the hidden_size attribute in order to make Dinat work with VisionEncoderDecoderModel
							# this indicates the channel dimension after the last stage of the model
							UpperCAmelCase_    :      Optional[int]            =						int(embed_dim * 2 ** (len(_lowerCAmelCase   ) - 1)   )
							UpperCAmelCase_    :      Dict            =						layer_scale_init_value
							UpperCAmelCase_    :      Union[str, Any]            =						['stem'] + [f"stage{idx}" for idx in range(1				,		len(_lowerCAmelCase   ) + 1   )]
							UpperCAmelCase_       ,  UpperCAmelCase_    :      List[Any]            =						get_aligned_output_features_output_indices(
							    out_features=_lowerCAmelCase				,		out_indices=_lowerCAmelCase				,		stage_names=self.stage_names   )












from __future__ import annotations

lowerCamelCase__ :   Optional[int]					=							[-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
lowerCamelCase__ :   List[Any]					=							[-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	list[float]							)					-> list[float]:
      SCREAMING_SNAKE_CASE_							=			[]
      SCREAMING_SNAKE_CASE_							=			len(__UpperCAmelCase							)

      for i in range(__UpperCAmelCase							):
            SCREAMING_SNAKE_CASE_							=			-1
            for j in range(i + 1			,			__UpperCAmelCase							):
                  if arr[i] < arr[j]:
                        SCREAMING_SNAKE_CASE_							=			arr[j]
                        break
            result.append(__UpperCAmelCase							)
      return result

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	list[float]							)					-> list[float]:
      SCREAMING_SNAKE_CASE_							=			[]
      for i, outer in enumerate(__UpperCAmelCase							):
            SCREAMING_SNAKE_CASE_							=			-1
            for inner in arr[i + 1 :]:
                  if outer < inner:
                        SCREAMING_SNAKE_CASE_							=			inner
                        break
            result.append(__UpperCAmelCase							)
      return result

def 					UpperCAmelCase_							(      __UpperCAmelCase						:	list[float]							)					-> list[float]:
      SCREAMING_SNAKE_CASE_							=			len(__UpperCAmelCase							)
      SCREAMING_SNAKE_CASE_							=			[]
      SCREAMING_SNAKE_CASE_							=			[-1] * arr_size

      for index in reversed(range(__UpperCAmelCase							)							):
            if stack:
                  while stack[-1] <= arr[index]:
                        stack.pop()
                        if not stack:
                              break
            if stack:
                  SCREAMING_SNAKE_CASE_							=			stack[-1]
            stack.append(arr[index]							)
      return result


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

   testmod()
   print(next_greatest_element_slow(arr))
   print(next_greatest_element_fast(arr))
   print(next_greatest_element(arr))

   lowerCamelCase__ :   List[str]					=							(
       'from __main__ import arr, next_greatest_element_slow, '
       'next_greatest_element_fast, next_greatest_element'
   )
   print(
       'next_greatest_element_slow():',
       timeit('next_greatest_element_slow(arr)', setup=setup),
   )
   print(
       'next_greatest_element_fast():',
       timeit('next_greatest_element_fast(arr)', setup=setup),
   )
   print(
       '     next_greatest_element():',
       timeit('next_greatest_element(arr)', setup=setup),
   )