'''simple docstring'''







import random


def    lowerCamelCase       (			UpperCAmelCase__				:  int		)			->	bool:


							'''simple docstring'''






							SCREAMING_SNAKE_CASE__     :Tuple						    = num - 1
							SCREAMING_SNAKE_CASE__     :List[Any]						    = 0

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

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


def    lowerCamelCase       (			UpperCAmelCase__				:  int		)			->	bool:


							'''simple docstring'''






							if num < 2:
														return False

							SCREAMING_SNAKE_CASE__     :List[str]						    = [
							    2,
							    3,
							    5,
							    7,
							    1_1,
							    1_3,
							    1_7,
							    1_9,
							    2_3,
							    2_9,
							    3_1,
							    3_7,
							    4_1,
							    4_3,
							    4_7,
							    5_3,
							    5_9,
							    6_1,
							    6_7,
							    7_1,
							    7_3,
							    7_9,
							    8_3,
							    8_9,
							    9_7,
							    1_0_1,
							    1_0_3,
							    1_0_7,
							    1_0_9,
							    1_1_3,
							    1_2_7,
							    1_3_1,
							    1_3_7,
							    1_3_9,
							    1_4_9,
							    1_5_1,
							    1_5_7,
							    1_6_3,
							    1_6_7,
							    1_7_3,
							    1_7_9,
							    1_8_1,
							    1_9_1,
							    1_9_3,
							    1_9_7,
							    1_9_9,
							    2_1_1,
							    2_2_3,
							    2_2_7,
							    2_2_9,
							    2_3_3,
							    2_3_9,
							    2_4_1,
							    2_5_1,
							    2_5_7,
							    2_6_3,
							    2_6_9,
							    2_7_1,
							    2_7_7,
							    2_8_1,
							    2_8_3,
							    2_9_3,
							    3_0_7,
							    3_1_1,
							    3_1_3,
							    3_1_7,
							    3_3_1,
							    3_3_7,
							    3_4_7,
							    3_4_9,
							    3_5_3,
							    3_5_9,
							    3_6_7,
							    3_7_3,
							    3_7_9,
							    3_8_3,
							    3_8_9,
							    3_9_7,
							    4_0_1,
							    4_0_9,
							    4_1_9,
							    4_2_1,
							    4_3_1,
							    4_3_3,
							    4_3_9,
							    4_4_3,
							    4_4_9,
							    4_5_7,
							    4_6_1,
							    4_6_3,
							    4_6_7,
							    4_7_9,
							    4_8_7,
							    4_9_1,
							    4_9_9,
							    5_0_3,
							    5_0_9,
							    5_2_1,
							    5_2_3,
							    5_4_1,
							    5_4_7,
							    5_5_7,
							    5_6_3,
							    5_6_9,
							    5_7_1,
							    5_7_7,
							    5_8_7,
							    5_9_3,
							    5_9_9,
							    6_0_1,
							    6_0_7,
							    6_1_3,
							    6_1_7,
							    6_1_9,
							    6_3_1,
							    6_4_1,
							    6_4_3,
							    6_4_7,
							    6_5_3,
							    6_5_9,
							    6_6_1,
							    6_7_3,
							    6_7_7,
							    6_8_3,
							    6_9_1,
							    7_0_1,
							    7_0_9,
							    7_1_9,
							    7_2_7,
							    7_3_3,
							    7_3_9,
							    7_4_3,
							    7_5_1,
							    7_5_7,
							    7_6_1,
							    7_6_9,
							    7_7_3,
							    7_8_7,
							    7_9_7,
							    8_0_9,
							    8_1_1,
							    8_2_1,
							    8_2_3,
							    8_2_7,
							    8_2_9,
							    8_3_9,
							    8_5_3,
							    8_5_7,
							    8_5_9,
							    8_6_3,
							    8_7_7,
							    8_8_1,
							    8_8_3,
							    8_8_7,
							    9_0_7,
							    9_1_1,
							    9_1_9,
							    9_2_9,
							    9_3_7,
							    9_4_1,
							    9_4_7,
							    9_5_3,
							    9_6_7,
							    9_7_1,
							    9_7_7,
							    9_8_3,
							    9_9_1,
							    9_9_7,
							]

							if num in low_primes:
														return True

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

							return rabin_miller(_snake_case		)


def    lowerCamelCase       (			UpperCAmelCase__				:  int = 1_0_2_4		)			->	int:


							'''simple docstring'''






							while True:
														SCREAMING_SNAKE_CASE__     :Union[str, Any]						    = random.randrange(2 ** (keysize - 1)				,						2 ** (keysize)		)
														if is_prime_low_num(_snake_case		):
																					return num


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












"""simple docstring"""

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


a							      =     logging.get_logger(__name__)

a							      =     {
    '''facebook/s2t-small-librispeech-asr''': (
        '''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config.json'''
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech_to_text
}





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	str     =      '''speech_to_text'''
 UpperCAmelCase       :	List[Any]     =      ['''past_key_values''']
 UpperCAmelCase       :	Tuple     =      {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}

 def __init__(					self			:			int       ,				_UpperCAmelCase			:			Union[str, Any]=10_000       ,				_UpperCAmelCase			:			Tuple=12       ,				_UpperCAmelCase			:			int=2_048       ,				_UpperCAmelCase			:			Optional[Any]=4       ,				_UpperCAmelCase			:			List[str]=6       ,				_UpperCAmelCase			:			Tuple=2_048       ,				_UpperCAmelCase			:			str=4       ,				_UpperCAmelCase			:			int=0.0       ,				_UpperCAmelCase			:			Dict=0.0       ,				_UpperCAmelCase			:			Optional[int]=True       ,				_UpperCAmelCase			:			Optional[Any]=True       ,				_UpperCAmelCase			:			Union[str, Any]="relu"       ,				_UpperCAmelCase			:			List[Any]=256       ,				_UpperCAmelCase			:			Optional[int]=0.1       ,				_UpperCAmelCase			:			Any=0.0       ,				_UpperCAmelCase			:			Dict=0.0       ,				_UpperCAmelCase			:			str=0.02       ,				_UpperCAmelCase			:			Any=2       ,				_UpperCAmelCase			:			Dict=True       ,				_UpperCAmelCase			:			List[str]=1       ,				_UpperCAmelCase			:			Tuple=0       ,				_UpperCAmelCase			:			Tuple=2       ,				_UpperCAmelCase			:			List[str]=6_000       ,				_UpperCAmelCase			:			Optional[Any]=1_024       ,				_UpperCAmelCase			:			Optional[Any]=2       ,				_UpperCAmelCase			:			Any=(5, 5)       ,				_UpperCAmelCase			:			int=1_024       ,				_UpperCAmelCase			:			str=80       ,				_UpperCAmelCase			:			Any=1       ,				**_UpperCAmelCase			:			Tuple       ,				):
       _A     =  vocab_size
       _A     =  d_model
       _A     =  encoder_ffn_dim
       _A     =  encoder_layers
       _A     =  encoder_attention_heads
       _A     =  decoder_ffn_dim
       _A     =  decoder_layers
       _A     =  decoder_attention_heads
       _A     =  dropout
       _A     =  attention_dropout
       _A     =  activation_dropout
       _A     =  activation_function
       _A     =  init_std
       _A     =  encoder_layerdrop
       _A     =  decoder_layerdrop
       _A     =  use_cache
       _A     =  encoder_layers
       _A     =  scale_embedding  # scale factor will be sqrt(d_model) if True
       _A     =  max_source_positions
       _A     =  max_target_positions
       _A     =  num_conv_layers
       _A     =  list(_UpperCAmelCase						)
       _A     =  conv_channels
       _A     =  input_feat_per_channel
       _A     =  input_channels

       if len(self.conv_kernel_sizes						) != self.num_conv_layers:
             raise ValueError(
                 'Configuration for convolutional module is incorrect. '
                 'It is required that `len(config.conv_kernel_sizes)` == `config.num_conv_layers` '
                 F'''but is `len(config.conv_kernel_sizes) = {len(self.conv_kernel_sizes						)}`, '''
                 F'''`config.num_conv_layers = {self.num_conv_layers}`.'''						)

       super().__init__(
           pad_token_id=_UpperCAmelCase       ,				bos_token_id=_UpperCAmelCase       ,				eos_token_id=_UpperCAmelCase       ,				is_encoder_decoder=_UpperCAmelCase       ,				decoder_start_token_id=_UpperCAmelCase       ,				**_UpperCAmelCase       ,				)

