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


SCREAMING_SNAKE_CASE		:     Union[str, Any]         =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:     Union[str, Any]         =	{
    "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        UpperCamelCase						(				UpperCamelCase_				):
						a__		:Optional[int]      =			'speech_to_text_2'
						a__		:int      =			['past_key_values']
						a__		:Tuple      =			{'num_attention_heads': 'decoder_attention_heads', 'hidden_size': 'd_model'}





						def __init__(self			,     __UpperCamelCase=10_000			,     __UpperCamelCase=6			,     __UpperCamelCase=2_048			,     __UpperCamelCase=4			,     __UpperCamelCase=0.0			,     __UpperCamelCase=True			,     __UpperCamelCase="relu"			,     __UpperCamelCase=256			,     __UpperCamelCase=0.1			,     __UpperCamelCase=0.0			,     __UpperCamelCase=0.0			,     __UpperCamelCase=0.02			,     __UpperCamelCase=2			,     __UpperCamelCase=True			,     __UpperCamelCase=1			,     __UpperCamelCase=0			,     __UpperCamelCase=2			,     __UpperCamelCase=1_024			,     **__UpperCamelCase			,     )				->				int:
												UpperCamelCase_		:							Optional[Any]  =		vocab_size
												UpperCamelCase_		:							Tuple  =		d_model
												UpperCamelCase_		:							Optional[int]  =		decoder_ffn_dim
												UpperCamelCase_		:							Optional[int]  =		decoder_layers
												UpperCamelCase_		:							List[Any]  =		decoder_attention_heads
												UpperCamelCase_		:							str  =		dropout
												UpperCamelCase_		:							Dict  =		attention_dropout
												UpperCamelCase_		:							Dict  =		activation_dropout
												UpperCamelCase_		:							int  =		activation_function
												UpperCamelCase_		:							int  =		init_std
												UpperCamelCase_		:							Dict  =		decoder_layerdrop
												UpperCamelCase_		:							List[str]  =		use_cache
												UpperCamelCase_		:							List[str]  =		decoder_layers
												UpperCamelCase_		:							str  =		scale_embedding  # scale factor will be sqrt(d_model) if True
												UpperCamelCase_		:							Dict  =		max_target_positions

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










import warnings

from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor


lowerCamelCase		   =			logging.get_logger(__name__)




class A    (  UpperCamelCase_	):






      def __init__(   self		:	Optional[Any]     ,  *lowercase_		:	str     ,  **lowercase_		:	List[Any]					)   ->		None:
             """simple docstring"""




             warnings.warn(
                 'The class MobileViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
                 ' Please use MobileViTImageProcessor instead.'     ,  lowercase_     ,  )
             super().__init__(*lowercase_     ,  **lowercase_					)


