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


__A							=logging.get_logger(__name__)

__A							={
    '''speechbrain/m-ctc-t-large''': '''https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json''',
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}




class        _SCREAMING_SNAKE_CASE	( snake_case_		):
	lowerCAmelCase__   =					'mctct'



	def __init__(       self		,    lowercase=8065		,    lowercase=1536		,    lowercase=36		,    lowercase=6144		,    lowercase=4		,    lowercase=384		,    lowercase=920		,    lowercase=1e-5		,    lowercase=0.3		,    lowercase="relu"		,    lowercase=0.0_2		,    lowercase=0.3		,    lowercase=0.3		,    lowercase=1		,    lowercase=0		,    lowercase=2		,    lowercase=1		,    lowercase=0.3		,    lowercase=1		,    lowercase=(7,)		,    lowercase=(3,)		,    lowercase=80		,    lowercase=1		,    lowercase=None		,    lowercase="sum"		,    lowercase=False		,    **lowercase		,    )							->			Dict:
					super().__init__(**lowercase		,    pad_token_id=lowercase		,    bos_token_id=lowercase		,    eos_token_id=lowercase					)
					lowerCamelCase_         =     vocab_size
					lowerCamelCase_         =     hidden_size
					lowerCamelCase_         =     num_hidden_layers
					lowerCamelCase_         =     intermediate_size
					lowerCamelCase_         =     num_attention_heads
					lowerCamelCase_         =     attention_head_dim
					lowerCamelCase_         =     max_position_embeddings
					lowerCamelCase_         =     layer_norm_eps
					lowerCamelCase_         =     layerdrop
					lowerCamelCase_         =     hidden_act
					lowerCamelCase_         =     initializer_range
					lowerCamelCase_         =     hidden_dropout_prob
					lowerCamelCase_         =     attention_probs_dropout_prob
					lowerCamelCase_         =     pad_token_id
					lowerCamelCase_         =     bos_token_id
					lowerCamelCase_         =     eos_token_id
					lowerCamelCase_         =     conv_glu_dim
					lowerCamelCase_         =     conv_dropout
					lowerCamelCase_         =     num_conv_layers
					lowerCamelCase_         =     input_feat_per_channel
					lowerCamelCase_         =     input_channels
					lowerCamelCase_         =     conv_channels
					lowerCamelCase_         =     ctc_loss_reduction
					lowerCamelCase_         =     ctc_zero_infinity

					# prevents config testing fail with exporting to json
					lowerCamelCase_         =     list(lowercase					)
					lowerCamelCase_         =     list(lowercase					)

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




from __future__ import annotations

import math





def      lowerCamelCase_					(							lowerCamelCase__       ):

				if 1 < number < 4:
								# 2 and 3 are primes
								return True
				elif number < 2 or number % 2 == 0 or number % 3 == 0:
								# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
								return False

				# All primes number are in format of 6k +/- 1
				for i in range(5      ,					int(math.sqrt(lowerCamelCase__       ) + 1       )      ,					6       ):
								if number % i == 0 or number % (i + 2) == 0:
												return False
				return True


__A							=[num for num in range(3, 1_0_0_0_0_1, 2) if not is_prime(num)]





def      lowerCamelCase_					(							lowerCamelCase__       ):
				if not isinstance(lowerCamelCase__      ,					lowerCamelCase__       ):
								raise ValueError("n must be an integer"       )
				if n <= 0:
								raise ValueError("n must be >= 0"       )

				lowerCamelCase_         =     []
				for num in range(len(lowerCamelCase__       )       ):
								lowerCamelCase_         =     0
								while 2 * i * i <= odd_composites[num]:
												lowerCamelCase_         =     odd_composites[num] - 2 * i * i
												if is_prime(lowerCamelCase__       ):
																break
												i += 1
								else:
												list_nums.append(odd_composites[num]       )
												if len(lowerCamelCase__       ) == n:
																return list_nums

				return []





def      lowerCamelCase_					(							):
				return compute_nums(1       )[0]


if __name__ == "__main__":
			print(F"""{solution() = }""")


