


"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


lowercase_			     =  logging.get_logger(__name__)

lowercase_			     =  {
    "facebook/data2vec-text-base": "https://huggingface.co/data2vec/resolve/main/config.json",
}
class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		__UpperCAmelCase		:			Optional[Any]										=				'data2vec-text'

		def __init__(  self							, _a=30_522							, _a=768							, _a=12							, _a=12							, _a=3_072							, _a="gelu"							, _a=0.1							, _a=0.1							, _a=512							, _a=2							, _a=0.02							, _a=1E-12							, _a=1							, _a=0							, _a=2							, _a="absolute"							, _a=True							, _a=None							, **_a							, ):
				super().__init__(pad_token_id=_a							, bos_token_id=_a							, eos_token_id=_a							, **_a      )

				__a           =			vocab_size
				__a           =			hidden_size
				__a           =			num_hidden_layers
				__a           =			num_attention_heads
				__a           =			hidden_act
				__a           =			intermediate_size
				__a           =			hidden_dropout_prob
				__a           =			attention_probs_dropout_prob
				__a           =			max_position_embeddings
				__a           =			type_vocab_size
				__a           =			initializer_range
				__a           =			layer_norm_eps
				__a           =			position_embedding_type
				__a           =			use_cache
				__a           =			classifier_dropout







class 					__lowerCAmelCase					(   __SCREAMING_SNAKE_CASE       ):


		'''simple docstring'''



		@property
		def 			__UpperCAmelCase       (  self      ):
				if self.task == "multiple-choice":
						__a           =			{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
				else:
						__a           =			{0: '''batch''', 1: '''sequence'''}
				return OrderedDict(
				    [
				        ('''input_ids''', dynamic_axis),
				        ('''attention_mask''', dynamic_axis),
				    ]      )










"""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()






