


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


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

snake_case							:       Union[str, Any]										=	{
    '''MIT/ast-finetuned-audioset-10-10-0.4593''': (
        '''https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json'''
    ),
}







class 						_snake_case    ( _snake_case				):
 SCREAMING_SNAKE_CASE__ =			'audio-spectrogram-transformer'




 def __init__(						self   ,    _lowerCamelCase=768   ,    _lowerCamelCase=12   ,    _lowerCamelCase=12   ,    _lowerCamelCase=3072   ,    _lowerCamelCase="gelu"   ,    _lowerCamelCase=0.0   ,    _lowerCamelCase=0.0   ,    _lowerCamelCase=0.02   ,    _lowerCamelCase=1e-12   ,    _lowerCamelCase=16   ,    _lowerCamelCase=True   ,    _lowerCamelCase=10   ,    _lowerCamelCase=10   ,    _lowerCamelCase=1024   ,    _lowerCamelCase=128   ,    **_lowerCamelCase   ,    ):
       super().__init__(**_lowerCamelCase       )

       a		:int									=			hidden_size
       a		:int									=			num_hidden_layers
       a		:int									=			num_attention_heads
       a		:str									=			intermediate_size
       a		:Optional[int]									=			hidden_act
       a		:Optional[Any]									=			hidden_dropout_prob
       a		:Optional[Any]									=			attention_probs_dropout_prob
       a		:Tuple									=			initializer_range
       a		:Optional[int]									=			layer_norm_eps
       a		:Optional[Any]									=			patch_size
       a		:Tuple									=			qkv_bias
       a		:List[str]									=			frequency_stride
       a		:Optional[Any]									=			time_stride
       a		:int									=			max_length
       a		:int									=			num_mel_bins









import functools
import operator

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


snake_case							:       Optional[int]										=	logging.get_logger(__name__)

snake_case							:       Optional[int]										=	{
    '''microsoft/unispeech-large-1500h-cv''': (
        '''https://huggingface.co/microsoft/unispeech-large-1500h-cv/resolve/main/config.json'''
    ),
    # See all UniSpeech models at https://huggingface.co/models?filter=unispeech
}







class 						_snake_case    ( _snake_case				):
 SCREAMING_SNAKE_CASE__ =			'unispeech'




 def __init__(						self   ,    _lowerCamelCase=32   ,    _lowerCamelCase=768   ,    _lowerCamelCase=12   ,    _lowerCamelCase=12   ,    _lowerCamelCase=3072   ,    _lowerCamelCase="gelu"   ,    _lowerCamelCase=0.1   ,    _lowerCamelCase=0.1   ,    _lowerCamelCase=0.1   ,    _lowerCamelCase=0.0   ,    _lowerCamelCase=0.0   ,    _lowerCamelCase=0.1   ,    _lowerCamelCase=0.1   ,    _lowerCamelCase=0.02   ,    _lowerCamelCase=1e-5   ,    _lowerCamelCase="group"   ,    _lowerCamelCase="gelu"   ,    _lowerCamelCase=(512, 512, 512, 512, 512, 512, 512)   ,    _lowerCamelCase=(5, 2, 2, 2, 2, 2, 2)   ,    _lowerCamelCase=(10, 3, 3, 3, 3, 2, 2)   ,    _lowerCamelCase=False   ,    _lowerCamelCase=128   ,    _lowerCamelCase=16   ,    _lowerCamelCase=False   ,    _lowerCamelCase=True   ,    _lowerCamelCase=0.05   ,    _lowerCamelCase=10   ,    _lowerCamelCase=2   ,    _lowerCamelCase=0.0   ,    _lowerCamelCase=10   ,    _lowerCamelCase=0   ,    _lowerCamelCase=320   ,    _lowerCamelCase=2   ,    _lowerCamelCase=0.1   ,    _lowerCamelCase=100   ,    _lowerCamelCase=256   ,    _lowerCamelCase=256   ,    _lowerCamelCase=0.1   ,    _lowerCamelCase="mean"   ,    _lowerCamelCase=False   ,    _lowerCamelCase=False   ,    _lowerCamelCase=256   ,    _lowerCamelCase=80   ,    _lowerCamelCase=0   ,    _lowerCamelCase=1   ,    _lowerCamelCase=2   ,    _lowerCamelCase=0.5   ,    **_lowerCamelCase   ,    ):
       super().__init__(**_lowerCamelCase   ,    pad_token_id=_lowerCamelCase   ,    bos_token_id=_lowerCamelCase   ,    eos_token_id=_lowerCamelCase       )
       a		:Any									=			hidden_size
       a		:str									=			feat_extract_norm
       a		:List[Any]									=			feat_extract_activation
       a		:Tuple									=			list(_lowerCamelCase       )
       a		:Any									=			list(_lowerCamelCase       )
       a		:List[Any]									=			list(_lowerCamelCase       )
       a		:Union[str, Any]									=			conv_bias
       a		:str									=			num_conv_pos_embeddings
       a		:str									=			num_conv_pos_embedding_groups
       a		:Tuple									=			len(self.conv_dim       )
       a		:int									=			num_hidden_layers
       a		:Any									=			intermediate_size
       a		:Optional[Any]									=			hidden_act
       a		:Tuple									=			num_attention_heads
       a		:Any									=			hidden_dropout
       a		:Any									=			attention_dropout
       a		:Optional[Any]									=			activation_dropout
       a		:Optional[Any]									=			feat_proj_dropout
       a		:Any									=			final_dropout
       a		:int									=			layerdrop
       a		:int									=			layer_norm_eps
       a		:Dict									=			initializer_range
       a		:Dict									=			num_ctc_classes
       a		:Optional[Any]									=			vocab_size
       a		:str									=			do_stable_layer_norm
       a		:Tuple									=			use_weighted_layer_sum
       a		:Any									=			classifier_proj_size

       if (
           (len(self.conv_stride       ) != self.num_feat_extract_layers)
           or (len(self.conv_kernel       ) != self.num_feat_extract_layers)
           or (len(self.conv_dim       ) != self.num_feat_extract_layers)
       ):
             raise ValueError(
                 '''Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =='''
                 ''' `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ='''
                 F''' {len(self.conv_dim       )}`, `len(config.conv_stride) = {len(self.conv_stride       )}`,'''
                 F''' `len(config.conv_kernel) = {len(self.conv_kernel       )}`.'''       )

       # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
       a		:List[Any]									=			apply_spec_augment
       a		:Any									=			mask_time_prob
       a		:Union[str, Any]									=			mask_time_length
       a		:str									=			mask_time_min_masks
       a		:Tuple									=			mask_feature_prob
       a		:Dict									=			mask_feature_length
       a		:int									=			mask_feature_min_masks

       # parameters for pretraining with codevector quantized representations
       a		:Union[str, Any]									=			num_codevectors_per_group
       a		:Dict									=			num_codevector_groups
       a		:List[Any]									=			contrastive_logits_temperature
       a		:Union[str, Any]									=			feat_quantizer_dropout
       a		:Optional[Any]									=			num_negatives
       a		:Tuple									=			codevector_dim
       a		:Optional[Any]									=			proj_codevector_dim
       a		:Union[str, Any]									=			diversity_loss_weight

       # ctc loss
       a		:List[Any]									=			ctc_loss_reduction
       a		:Union[str, Any]									=			ctc_zero_infinity

       # pretraining loss
       a		:int									=			replace_prob




 @property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       return functools.reduce(operator.mul   ,    self.conv_stride   ,    1       )





