

"""simple docstring"""


import functools
import operator

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase													=logging.get_logger(__name__)

UpperCAmelCase													={
    "facebook/wav2vec2-base-960h": "https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/config.json",
    # See all Wav2Vec2 models at https://huggingface.co/models?filter=wav2vec2
}





class lowerCamelCase__   (				lowercase_    ):



    '''simple docstring'''




    _lowerCamelCase					=   '''wav2vec2'''




    def __init__( self ,lowerCamelCase_=3_2 ,lowerCamelCase_=7_6_8 ,lowerCamelCase_=1_2 ,lowerCamelCase_=1_2 ,lowerCamelCase_=3_0_7_2 ,lowerCamelCase_="gelu" ,lowerCamelCase_=0.1 ,lowerCamelCase_=0.1 ,lowerCamelCase_=0.1 ,lowerCamelCase_=0.0 ,lowerCamelCase_=0.0 ,lowerCamelCase_=0.1 ,lowerCamelCase_=0.1 ,lowerCamelCase_=0.02 ,lowerCamelCase_=1E-5 ,lowerCamelCase_="group" ,lowerCamelCase_="gelu" ,lowerCamelCase_=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2) ,lowerCamelCase_=(5, 2, 2, 2, 2, 2, 2) ,lowerCamelCase_=(1_0, 3, 3, 3, 3, 2, 2) ,lowerCamelCase_=False ,lowerCamelCase_=1_2_8 ,lowerCamelCase_=1_6 ,lowerCamelCase_=False ,lowerCamelCase_=True ,lowerCamelCase_=0.05 ,lowerCamelCase_=1_0 ,lowerCamelCase_=2 ,lowerCamelCase_=0.0 ,lowerCamelCase_=1_0 ,lowerCamelCase_=0 ,lowerCamelCase_=3_2_0 ,lowerCamelCase_=2 ,lowerCamelCase_=0.1 ,lowerCamelCase_=1_0_0 ,lowerCamelCase_=2_5_6 ,lowerCamelCase_=2_5_6 ,lowerCamelCase_=0.1 ,lowerCamelCase_="sum" ,lowerCamelCase_=False ,lowerCamelCase_=False ,lowerCamelCase_=2_5_6 ,lowerCamelCase_=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 1_5_0_0) ,lowerCamelCase_=(5, 3, 3, 1, 1) ,lowerCamelCase_=(1, 2, 3, 1, 1) ,lowerCamelCase_=5_1_2 ,lowerCamelCase_=0 ,lowerCamelCase_=1 ,lowerCamelCase_=2 ,lowerCamelCase_=False ,lowerCamelCase_=3 ,lowerCamelCase_=2 ,lowerCamelCase_=3 ,lowerCamelCase_=None ,lowerCamelCase_=None ,**lowerCamelCase_ ,)    ->      str:
          super().__init__(**lowerCamelCase_ ,pad_token_id=lowerCamelCase_ ,bos_token_id=lowerCamelCase_ ,eos_token_id=lowerCamelCase_    )
          A				  =		hidden_size
          A				  =		feat_extract_norm
          A				  =		feat_extract_activation
          A				  =		list(lowerCamelCase_    )
          A				  =		list(lowerCamelCase_    )
          A				  =		list(lowerCamelCase_    )
          A				  =		conv_bias
          A				  =		num_conv_pos_embeddings
          A				  =		num_conv_pos_embedding_groups
          A				  =		len(self.conv_dim    )
          A				  =		num_hidden_layers
          A				  =		intermediate_size
          A				  =		hidden_act
          A				  =		num_attention_heads
          A				  =		hidden_dropout
          A				  =		attention_dropout
          A				  =		activation_dropout
          A				  =		feat_proj_dropout
          A				  =		final_dropout
          A				  =		layerdrop
          A				  =		layer_norm_eps
          A				  =		initializer_range
          A				  =		vocab_size
          A				  =		do_stable_layer_norm
          A				  =		use_weighted_layer_sum

          if (
              (len(self.conv_stride    ) != self.num_feat_extract_layers)
              or (len(self.conv_kernel    ) != self.num_feat_extract_layers)
              or (len(self.conv_dim    ) != self.num_feat_extract_layers)
          ):
                raise ValueError(
                    """Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =="""
                    """ `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ="""
                    f' {len(self.conv_dim    )}`, `len(config.conv_stride) = {len(self.conv_stride    )}`,'
                    f' `len(config.conv_kernel) = {len(self.conv_kernel    )}`.'    )

          # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
          A				  =		apply_spec_augment
          A				  =		mask_time_prob
          A				  =		mask_time_length
          A				  =		mask_time_min_masks
          A				  =		mask_feature_prob
          A				  =		mask_feature_length
          A				  =		mask_feature_min_masks

          # parameters for pretraining with codevector quantized representations
          A				  =		num_codevectors_per_group
          A				  =		num_codevector_groups
          A				  =		contrastive_logits_temperature
          A				  =		feat_quantizer_dropout
          A				  =		num_negatives
          A				  =		codevector_dim
          A				  =		proj_codevector_dim
          A				  =		diversity_loss_weight

          # ctc loss
          A				  =		ctc_loss_reduction
          A				  =		ctc_zero_infinity

          # adapter
          A				  =		add_adapter
          A				  =		adapter_kernel_size
          A				  =		adapter_stride
          A				  =		num_adapter_layers
          A				  =		output_hidden_size or hidden_size
          A				  =		adapter_attn_dim

          # SequenceClassification-specific parameter. Feel free to ignore for other classes.
          A				  =		classifier_proj_size

          # XVector-specific parameters. Feel free to ignore for other classes.
          A				  =		list(lowerCamelCase_    )
          A				  =		list(lowerCamelCase_    )
          A				  =		list(lowerCamelCase_    )
          A				  =		xvector_output_dim




    @property
    def UpperCamelCase__		( self    )    ->      int:
          return functools.reduce(operator.mul ,self.conv_stride ,1    )











'''simple docstring'''




import random



def 		__A		(  lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				str		=			num - 1
		SCREAMING_SNAKE_CASE :				Union[str, Any]		=			0

		while s % 2 == 0:
				SCREAMING_SNAKE_CASE :				List[str]		=			s // 2
				t += 1

		for _ in range(5	):
				SCREAMING_SNAKE_CASE :				List[Any]		=			random.randrange(2			,			num - 1	)
				SCREAMING_SNAKE_CASE :				List[Any]		=			pow(lowerCamelCase_			,			lowerCamelCase_			,			lowerCamelCase_	)
				if v != 1:
						SCREAMING_SNAKE_CASE :				Tuple		=			0
						while v != (num - 1):
								if i == t - 1:
										return False
								else:
										SCREAMING_SNAKE_CASE :				Any		=			i + 1
										SCREAMING_SNAKE_CASE :				str		=			(v**2) % num
		return True



def 		__A		(  lowerCamelCase_	):


		"""simple docstring"""



		if num < 2:
				return False

		SCREAMING_SNAKE_CASE :				List[str]		=			[
		    2,
		    3,
		    5,
		    7,
		    11,
		    13,
		    17,
		    19,
		    23,
		    29,
		    31,
		    37,
		    41,
		    43,
		    47,
		    53,
		    59,
		    61,
		    67,
		    71,
		    73,
		    79,
		    83,
		    89,
		    97,
		    1_01,
		    1_03,
		    1_07,
		    1_09,
		    1_13,
		    1_27,
		    1_31,
		    1_37,
		    1_39,
		    1_49,
		    1_51,
		    1_57,
		    1_63,
		    1_67,
		    1_73,
		    1_79,
		    1_81,
		    1_91,
		    1_93,
		    1_97,
		    1_99,
		    2_11,
		    2_23,
		    2_27,
		    2_29,
		    2_33,
		    2_39,
		    2_41,
		    2_51,
		    2_57,
		    2_63,
		    2_69,
		    2_71,
		    2_77,
		    2_81,
		    2_83,
		    2_93,
		    3_07,
		    3_11,
		    3_13,
		    3_17,
		    3_31,
		    3_37,
		    3_47,
		    3_49,
		    3_53,
		    3_59,
		    3_67,
		    3_73,
		    3_79,
		    3_83,
		    3_89,
		    3_97,
		    4_01,
		    4_09,
		    4_19,
		    4_21,
		    4_31,
		    4_33,
		    4_39,
		    4_43,
		    4_49,
		    4_57,
		    4_61,
		    4_63,
		    4_67,
		    4_79,
		    4_87,
		    4_91,
		    4_99,
		    5_03,
		    5_09,
		    5_21,
		    5_23,
		    5_41,
		    5_47,
		    5_57,
		    5_63,
		    5_69,
		    5_71,
		    5_77,
		    5_87,
		    5_93,
		    5_99,
		    6_01,
		    6_07,
		    6_13,
		    6_17,
		    6_19,
		    6_31,
		    6_41,
		    6_43,
		    6_47,
		    6_53,
		    6_59,
		    6_61,
		    6_73,
		    6_77,
		    6_83,
		    6_91,
		    7_01,
		    7_09,
		    7_19,
		    7_27,
		    7_33,
		    7_39,
		    7_43,
		    7_51,
		    7_57,
		    7_61,
		    7_69,
		    7_73,
		    7_87,
		    7_97,
		    8_09,
		    8_11,
		    8_21,
		    8_23,
		    8_27,
		    8_29,
		    8_39,
		    8_53,
		    8_57,
		    8_59,
		    8_63,
		    8_77,
		    8_81,
		    8_83,
		    8_87,
		    9_07,
		    9_11,
		    9_19,
		    9_29,
		    9_37,
		    9_41,
		    9_47,
		    9_53,
		    9_67,
		    9_71,
		    9_77,
		    9_83,
		    9_91,
		    9_97,
		]

		if num in low_primes:
				return True

		for prime in low_primes:
				if (num % prime) == 0:
						return False

		return rabin_miller(lowerCamelCase_	)



def 		__A		(  lowerCamelCase_ = 10_24	):


		"""simple docstring"""



		while True:
				SCREAMING_SNAKE_CASE :				Optional[Any]		=			random.randrange(2 ** (keysize - 1)			,			2 ** (keysize)	)
				if is_prime_low_num(lowerCamelCase_	):
						return num


if __name__ == "__main__":
							__UpperCAmelCase            =       generate_large_prime()
							print(("""Prime number:""", num))
							print(("""is_prime_low_num:""", is_prime_low_num(num)))



