



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


__snake_case    :		List[Any]  =logging.get_logger(__name__)

__snake_case    :		List[str]  ={
    'shi-labs/nat-mini-in1k-224': 'https://huggingface.co/shi-labs/nat-mini-in1k-224/resolve/main/config.json',
    # See all Nat models at https://huggingface.co/models?filter=nat
}



class 	lowerCamelCase__      (							lowerCamelCase__				,    lowerCamelCase__):




		'''simple docstring'''



		snake_case_     ="""nat"""

		snake_case_     ={
		    """num_attention_heads""": """num_heads""",
		    """num_hidden_layers""": """num_layers""",
		}



		def __init__(self		,__lowerCamelCase=4		,__lowerCamelCase=3		,__lowerCamelCase=64		,__lowerCamelCase=[3, 4, 6, 5]		,__lowerCamelCase=[2, 4, 8, 16]		,__lowerCamelCase=7		,__lowerCamelCase=3.0		,__lowerCamelCase=True		,__lowerCamelCase=0.0		,__lowerCamelCase=0.0		,__lowerCamelCase=0.1		,__lowerCamelCase="gelu"		,__lowerCamelCase=0.02		,__lowerCamelCase=1e-5		,__lowerCamelCase=0.0		,__lowerCamelCase=None		,__lowerCamelCase=None		,**__lowerCamelCase		,)					->      str:

						"""simple docstring"""






						super().__init__(**_SCREAMING_SNAKE_CASE			)

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






def      lowerCAmelCase__		(   lowerCamelCase_		:		str = "The quick brown fox jumps over the lazy dog"	,):





				'''simple docstring'''

				lowerCAmelCase__					:    Any												=					set()

				# Replace all the whitespace in our sentence
				lowerCAmelCase__					:    List[Any]												=					input_str.replace(''' '''	,'''''')
				for alpha in input_str:
								if "a" <= alpha.lower() <= "z":
												frequency.add(alpha.lower())
				return len(lowerCamelCase_) == 26






def      lowerCAmelCase__		(   lowerCamelCase_		:		str = "The quick brown fox jumps over the lazy dog"	,):





				'''simple docstring'''

				lowerCAmelCase__					:    List[str]												=					[False] * 26
				for char in input_str:
								if char.islower():
												lowerCAmelCase__					:    Union[str, Any]												=					True
								elif char.isupper():
												lowerCAmelCase__					:    str												=					True
				return all(lowerCamelCase_)






def      lowerCAmelCase__		(   lowerCamelCase_		:		str = "The quick brown fox jumps over the lazy dog"	,):





				'''simple docstring'''

				return len({char for char in input_str.lower() if char.isalpha()}) == 26






def      lowerCAmelCase__		(   ):





				'''simple docstring'''

				from timeit import timeit

				lowerCAmelCase__					:    Optional[Any]												=					'''from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest'''
				print(timeit('''is_pangram()'''	,setup=lowerCamelCase_))
				print(timeit('''is_pangram_faster()'''	,setup=lowerCamelCase_))
				print(timeit('''is_pangram_fastest()'''	,setup=lowerCamelCase_))
				# 5.348480500048026, 2.6477354579837993, 1.8470395830227062
				# 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							benchmark()

