




"""simple docstring"""




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


lowerCAmelCase							:			str     							=							logging.get_logger(__name__)

lowerCAmelCase							:			List[str]     							=							{
    """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     __magic_name__							(       UpperCAmelCase__				):






				'''simple docstring'''
				__UpperCamelCase			  =						"mctct"





				def __init__(       self		, _a=8_065		, _a=1_536		, _a=36		, _a=6_144		, _a=4		, _a=384		, _a=920		, _a=1e-5		, _a=0.3		, _a="relu"		, _a=0.02		, _a=0.3		, _a=0.3		, _a=1		, _a=0		, _a=2		, _a=1		, _a=0.3		, _a=1		, _a=(7,)		, _a=(3,)		, _a=80		, _a=1		, _a=None		, _a="sum"		, _a=False		, **_a		, ):





							"""simple docstring"""
							super().__init__(**_a		, pad_token_id=_a		, bos_token_id=_a		, eos_token_id=_a )
							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(_a )
							lowerCamelCase			      =					list(_a )

							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}`.' )









"""simple docstring"""




from __future__ import annotations



def     a__ (				snake_case__       , snake_case__				)						->					bool:
			if len(snake_case__				) == 0:
						return False
			lowerCamelCase			      =					len(snake_case__				) // 2
			if a_list[midpoint] == item:
						return True
			if item < a_list[midpoint]:
						return binary_search(a_list[:midpoint]       , snake_case__				)
			else:
						return binary_search(a_list[midpoint + 1 :]       , snake_case__				)


if __name__ == "__main__":
					lowerCAmelCase							:			List[Any]     							=							input("""Enter numbers separated by comma:\n""").strip()
					lowerCAmelCase							:			Optional[Any]     							=							[int(item.strip()) for item in user_input.split(""",""")]
					lowerCAmelCase							:			Optional[int]     							=							int(input("""Enter the number to be found in the list:\n""").strip())
					lowerCAmelCase							:			Union[str, Any]     							=							"""""" if binary_search(sequence, target) else """not """
					print(F"""{target} was {not_str}found in {sequence}""")



