




"""simple docstring"""






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


lowercase__     						=						logging.get_logger(__name__)

lowercase__     						=						{
    """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'''



			lowerCamelCase__      =			"""speech_to_text_2"""
			lowerCamelCase__      =			["""past_key_values"""]
			lowerCamelCase__      =			{"""num_attention_heads""": """decoder_attention_heads""", """hidden_size""": """d_model"""}
			def __init__(  self  ,      lowercase=10000  ,      lowercase=6  ,      lowercase=2048  ,      lowercase=4  ,      lowercase=0.0  ,      lowercase=True  ,      lowercase="relu"  ,      lowercase=256  ,      lowercase=0.1  ,      lowercase=0.0  ,      lowercase=0.0  ,      lowercase=0.02  ,      lowercase=2  ,      lowercase=True  ,      lowercase=1  ,      lowercase=0  ,      lowercase=2  ,      lowercase=1024  ,      **lowercase  ,      ):
							_lowerCamelCase     :			Dict    =    vocab_size
							_lowerCamelCase     :			str    =    d_model
							_lowerCamelCase     :			List[Any]    =    decoder_ffn_dim
							_lowerCamelCase     :			Optional[int]    =    decoder_layers
							_lowerCamelCase     :			Union[str, Any]    =    decoder_attention_heads
							_lowerCamelCase     :			Dict    =    dropout
							_lowerCamelCase     :			Union[str, Any]    =    attention_dropout
							_lowerCamelCase     :			List[str]    =    activation_dropout
							_lowerCamelCase     :			Optional[int]    =    activation_function
							_lowerCamelCase     :			Union[str, Any]    =    init_std
							_lowerCamelCase     :			Optional[Any]    =    decoder_layerdrop
							_lowerCamelCase     :			Optional[int]    =    use_cache
							_lowerCamelCase     :			Any    =    decoder_layers
							_lowerCamelCase     :			Optional[int]    =    scale_embedding  # scale factor will be sqrt(d_model) if True
							_lowerCamelCase     :			Union[str, Any]    =    max_target_positions

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






'''simple docstring'''







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


lowerCAmelCase_					:    Dict      	=			logging.get_logger(__name__)

lowerCAmelCase_					:    int      	=			{
    'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json',
}
class 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_      ):






				"""simple docstring"""







				__a            ='gpt_bigcode'
				__a            =['past_key_values']
				__a            ={
				    'hidden_size': 'n_embd',
				    'max_position_embeddings': 'n_positions',
				    'num_attention_heads': 'n_head',
				    'num_hidden_layers': 'n_layer',
				}




				def __init__(  self     :					Optional[Any]					,				__a     :					Tuple=5_02_57					,				__a     :					str=10_24					,				__a     :					Dict=7_68					,				__a     :					Tuple=12					,				__a     :					str=12					,				__a     :					Optional[int]=None					,				__a     :					Dict="gelu_pytorch_tanh"					,				__a     :					Tuple=0.1					,				__a     :					Tuple=0.1					,				__a     :					Union[str, Any]=0.1					,				__a     :					Tuple=1e-5					,				__a     :					str=0.02					,				__a     :					Dict=True					,				__a     :					Union[str, Any]=True					,				__a     :					Optional[int]=5_02_56					,				__a     :					Optional[int]=5_02_56					,				__a     :					Union[str, Any]=True					,				__a     :					Dict=True					,				__a     :					Union[str, Any]=True					,				**__a     :					List[Any]					,				):
								_a								= vocab_size
								_a								= n_positions
								_a								= n_embd
								_a								= n_layer
								_a								= n_head
								_a								= n_inner
								_a								= activation_function
								_a								= resid_pdrop
								_a								= embd_pdrop
								_a								= attn_pdrop
								_a								= layer_norm_epsilon
								_a								= initializer_range
								_a								= scale_attn_weights
								_a								= use_cache
								_a								= attention_softmax_in_fpaa
								_a								= scale_attention_softmax_in_fpaa
								_a								= multi_query

								_a								= bos_token_id
								_a								= eos_token_id

								super().__init__(bos_token_id=__a					,				eos_token_id=__a					,				**__a					)
