


"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase_			     =  logging.get_logger(__name__)

lowercase_			     =  {
    "google/mobilenet_v1_1.0_224": "https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json",
    "google/mobilenet_v1_0.75_192": "https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}
class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		__UpperCAmelCase		:			Optional[int]										=				'mobilenet_v1'

		def __init__(  self							, _a=3							, _a=224							, _a=1.0							, _a=8							, _a="relu6"							, _a=True							, _a=0.999							, _a=0.02							, _a=0.001							, **_a							, ):
				super().__init__(**_a      )

				if depth_multiplier <= 0:
						raise ValueError('''depth_multiplier must be greater than zero.'''      )

				__a           =			num_channels
				__a           =			image_size
				__a           =			depth_multiplier
				__a           =			min_depth
				__a           =			hidden_act
				__a           =			tf_padding
				__a           =			classifier_dropout_prob
				__a           =			initializer_range
				__a           =			layer_norm_eps







class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		__UpperCAmelCase		:			Tuple										=				version.parse('1.11'       )

		@property
		def 			__UpperCAmelCase       (  self      ):
				return OrderedDict([('''pixel_values''', {0: '''batch'''})]      )

		@property
		def 			__UpperCAmelCase       (  self      ):
				if self.task == "image-classification":
						return OrderedDict([('''logits''', {0: '''batch'''})]      )
				else:
						return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]      )





		@property
		def 			__UpperCAmelCase       (  self      ):
				return 1E-4










"""simple docstring"""




def        lowercase							(		lowerCAmelCase__ :     str = "The quick brown fox jumps over the lazy dog"    ,					) ->      bool:
		__a           =			set()

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

def        lowercase							(		lowerCAmelCase__ :     str = "The quick brown fox jumps over the lazy dog"    ,					) ->      bool:
		__a           =			[False] * 26
		for char in input_str:
				if char.islower():
						__a           =			True
				elif char.isupper():
						__a           =			True
		return all(lowerCAmelCase__			)

def        lowercase							(		lowerCAmelCase__ :     str = "The quick brown fox jumps over the lazy dog"    ,					) ->      bool:
		return len({char for char in input_str.lower() if char.isalpha()}			) == 26

def        lowercase							(		) ->      None:
		from timeit import timeit

		__a           =			'''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()






