




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__(					__lowerCamelCase):
      UpperCAmelCase__      :	List[str]    		=   'speech_to_text_2'
      UpperCAmelCase__      :	Dict    		=   ['past_key_values']
      UpperCAmelCase__      :	Tuple    		=   {'num_attention_heads': 'decoder_attention_heads', 'hidden_size': 'd_model'}
      def __init__(				self: Optional[int]    ,       UpperCamelCase_: List[str]=1_00_00    ,       UpperCamelCase_: int=6    ,       UpperCamelCase_: Dict=20_48    ,       UpperCamelCase_: Tuple=4    ,       UpperCamelCase_: List[Any]=0.0    ,       UpperCamelCase_: Union[str, Any]=True    ,       UpperCamelCase_: int="relu"    ,       UpperCamelCase_: Optional[Any]=2_56    ,       UpperCamelCase_: Tuple=0.1    ,       UpperCamelCase_: Optional[int]=0.0    ,       UpperCamelCase_: Union[str, Any]=0.0    ,       UpperCamelCase_: int=0.02    ,       UpperCamelCase_: str=2    ,       UpperCamelCase_: Optional[int]=True    ,       UpperCamelCase_: Optional[Any]=1    ,       UpperCamelCase_: Optional[int]=0    ,       UpperCamelCase_: Any=2    ,       UpperCamelCase_: Optional[int]=10_24    ,       **UpperCamelCase_: Optional[Any]    ,       ):
             __lowerCamelCase   =						vocab_size
             __lowerCamelCase   =						d_model
             __lowerCamelCase   =						decoder_ffn_dim
             __lowerCamelCase   =						decoder_layers
             __lowerCamelCase   =						decoder_attention_heads
             __lowerCamelCase   =						dropout
             __lowerCamelCase   =						attention_dropout
             __lowerCamelCase   =						activation_dropout
             __lowerCamelCase   =						activation_function
             __lowerCamelCase   =						init_std
             __lowerCamelCase   =						decoder_layerdrop
             __lowerCamelCase   =						use_cache
             __lowerCamelCase   =						decoder_layers
             __lowerCamelCase   =						scale_embedding  # scale factor will be sqrt(d_model) if True
             __lowerCamelCase   =						max_target_positions

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





snake_case				:    str       				=     '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

snake_case				:    List[Any]       				=     [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
snake_case				:    int       				=     {
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}





