





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


UpperCamelCase_												=	logging.get_logger(__name__)

UpperCamelCase_												=	{
    'facebook/s2t-wav2vec2-large-en-de': (
        'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech2text2
}

class     snake_case_		(   _SCREAMING_SNAKE_CASE							):






 '''simple docstring'''





 __UpperCamelCase       =      """speech_to_text_2"""
 __UpperCamelCase       =      ["""past_key_values"""]
 __UpperCamelCase       =      {"""num_attention_heads""": """decoder_attention_heads""", """hidden_size""": """d_model"""}

 def __init__(  self,		A_=1_0000,		A_=6,		A_=2048,		A_=4,		A_=0.0,		A_=True,		A_="relu",		A_=256,		A_=0.1,		A_=0.0,		A_=0.0,		A_=0.02,		A_=2,		A_=True,		A_=1,		A_=0,		A_=2,		A_=1024,		**A_,		)	->       Any:
    UpperCAmelCase__						=vocab_size
    UpperCAmelCase__						=d_model
    UpperCAmelCase__						=decoder_ffn_dim
    UpperCAmelCase__						=decoder_layers
    UpperCAmelCase__						=decoder_attention_heads
    UpperCAmelCase__						=dropout
    UpperCAmelCase__						=attention_dropout
    UpperCAmelCase__						=activation_dropout
    UpperCAmelCase__						=activation_function
    UpperCAmelCase__						=init_std
    UpperCAmelCase__						=decoder_layerdrop
    UpperCAmelCase__						=use_cache
    UpperCAmelCase__						=decoder_layers
    UpperCAmelCase__						=scale_embedding  # scale factor will be sqrt(d_model) if True
    UpperCAmelCase__						=max_target_positions

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











"""simple docstring"""
from __future__ import annotations






def       __UpperCamelCase						(		snake_case__ , snake_case__       ):
	if len(snake_case__       ) == 0:
		return False
	A_		:    Union[str, Any]						     = 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       =				input("Enter numbers separated by comma:\n").strip()
							_lowerCAmelCase       =				[int(item.strip()) for item in user_input.split(",")]
							_lowerCAmelCase       =				int(input("Enter the number to be found in the list:\n").strip())
							_lowerCAmelCase       =				"" if binary_search(sequence, target) else "not "
							print(F'{target} was {not_str}found in {sequence}')

