



'''simple docstring'''




from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			A_     :						List[Any]     =					prime_factors(lowerCamelCase__   )
			if is_square_free(lowerCamelCase__   ):
						return -1 if len(lowerCamelCase__   ) % 2 else 1
			return 0


if __name__ == "__main__":
						import doctest

						doctest.testmod()




'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase							:Any       = logging.get_logger(__name__)

lowerCamelCase							:List[Any]       = {
    '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/config.json''',
    '''umberto-commoncrawl-cased-v1''': (
        '''https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'''
    ),
    '''umberto-wikipedia-uncased-v1''': (
        '''https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'''
    ),
}







class      _lowerCAmelCase							(      __UpperCAmelCase			):
	__SCREAMING_SNAKE_CASE       :		Optional[int]		      = 'camembert'


	def __init__(self	,				lowercase=30522	,				lowercase=768	,				lowercase=12	,				lowercase=12	,				lowercase=3072	,				lowercase="gelu"	,				lowercase=0.1	,				lowercase=0.1	,				lowercase=512	,				lowercase=2	,				lowercase=0.02	,				lowercase=1E-12	,				lowercase=1	,				lowercase=0	,				lowercase=2	,				lowercase="absolute"	,				lowercase=True	,				lowercase=None	,				**lowercase	,				):
				super().__init__(pad_token_id=lowercase	,				bos_token_id=lowercase	,				eos_token_id=lowercase	,				**lowercase							)

				A_     :						List[Any]     =					vocab_size
				A_     :						int     =					hidden_size
				A_     :						Dict     =					num_hidden_layers
				A_     :						Dict     =					num_attention_heads
				A_     :						Optional[Any]     =					hidden_act
				A_     :						str     =					intermediate_size
				A_     :						int     =					hidden_dropout_prob
				A_     :						List[Any]     =					attention_probs_dropout_prob
				A_     :						Optional[Any]     =					max_position_embeddings
				A_     :						Optional[int]     =					type_vocab_size
				A_     :						int     =					initializer_range
				A_     :						str     =					layer_norm_eps
				A_     :						int     =					position_embedding_type
				A_     :						Dict     =					use_cache
				A_     :						Any     =					classifier_dropout







class      _lowerCAmelCase							(      __UpperCAmelCase			):


	@property
	def    _a     (self							):
				if self.task == "multiple-choice":
							A_     :						Optional[Any]     =					{0: """batch""", 1: """choice""", 2: """sequence"""}
				else:
							A_     :						int     =					{0: """batch""", 1: """sequence"""}
				return OrderedDict(
				    [
				        ("""input_ids""", dynamic_axis),
				        ("""attention_mask""", dynamic_axis),
				    ]							)