





import math






def     lowerCamelCase__			(__lowerCamelCase	):
     _SCREAMING_SNAKE_CASE       :	Dict						    =							0
     _SCREAMING_SNAKE_CASE       :	int						    =							0
     while num > 0:
          _SCREAMING_SNAKE_CASE       :	Union[str, Any]						    =							num % 8
          _SCREAMING_SNAKE_CASE       :	Union[str, Any]						    =							octal + (remainder * math.floor(math.pow(10,       __lowercase	)	))
          counter += 1
          _SCREAMING_SNAKE_CASE       :	Optional[int]						    =							math.floor(num / 8	)  # basically /= 8 without remainder if any
          # This formatting removes trailing '.0' from `octal`.
     return f"""0o{int(__lowercase	)}"""






def     lowerCamelCase__			():
     print("\n2 in octal is:"	)
     print(decimal_to_octal(2	)	)  # = 2
     print("\n8 in octal is:"	)
     print(decimal_to_octal(8	)	)  # = 10
     print("\n65 in octal is:"	)
     print(decimal_to_octal(65	)	)  # = 101
     print("\n216 in octal is:"	)
     print(decimal_to_octal(216	)	)  # = 330
     print("\n512 in octal is:"	)
     print(decimal_to_octal(512	)	)  # = 1000
     print("\n"	)


if __name__ == "__main__":
       main()













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 			lowerCAmelCase__( __lowercase    ):






       '''simple docstring'''


       __snake_case 			=    'speech_to_text_2'
       __snake_case 			=    ['past_key_values']
       __snake_case 			=    {'num_attention_heads': 'decoder_attention_heads', 'hidden_size': 'd_model'}




       def __init__(      self    ,						__lowerCamelCase=1_0_0_0_0    ,						__lowerCamelCase=6    ,						__lowerCamelCase=2_0_4_8    ,						__lowerCamelCase=4    ,						__lowerCamelCase=0.0    ,						__lowerCamelCase=True    ,						__lowerCamelCase="relu"    ,						__lowerCamelCase=2_5_6    ,						__lowerCamelCase=0.1    ,						__lowerCamelCase=0.0    ,						__lowerCamelCase=0.0    ,						__lowerCamelCase=0.02    ,						__lowerCamelCase=2    ,						__lowerCamelCase=True    ,						__lowerCamelCase=1    ,						__lowerCamelCase=0    ,						__lowerCamelCase=2    ,						__lowerCamelCase=1_0_2_4    ,						**__lowerCamelCase    ,						)			->     Optional[int]:
            _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							vocab_size
            _SCREAMING_SNAKE_CASE       :	List[Any]						    =							d_model
            _SCREAMING_SNAKE_CASE       :	Dict						    =							decoder_ffn_dim
            _SCREAMING_SNAKE_CASE       :	Tuple						    =							decoder_layers
            _SCREAMING_SNAKE_CASE       :	List[str]						    =							decoder_attention_heads
            _SCREAMING_SNAKE_CASE       :	Optional[int]						    =							dropout
            _SCREAMING_SNAKE_CASE       :	Optional[int]						    =							attention_dropout
            _SCREAMING_SNAKE_CASE       :	List[Any]						    =							activation_dropout
            _SCREAMING_SNAKE_CASE       :	Dict						    =							activation_function
            _SCREAMING_SNAKE_CASE       :	Optional[int]						    =							init_std
            _SCREAMING_SNAKE_CASE       :	List[str]						    =							decoder_layerdrop
            _SCREAMING_SNAKE_CASE       :	int						    =							use_cache
            _SCREAMING_SNAKE_CASE       :	int						    =							decoder_layers
            _SCREAMING_SNAKE_CASE       :	Tuple						    =							scale_embedding  # scale factor will be sqrt(d_model) if True
            _SCREAMING_SNAKE_CASE       :	str						    =							max_target_positions

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