





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


a__: Tuple							   =						logging.get_logger(__name__)

a__: Optional[Any]							   =						{
    'speechbrain/m-ctc-t-large': 'https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json',
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}




class        SCREAMING_SNAKE_CASE__					(		UpperCamelCase__ ):
 __SCREAMING_SNAKE_CASE							=      '''mctct'''



 def __init__(				self,__lowerCamelCase=8065,__lowerCamelCase=1536,__lowerCamelCase=36,__lowerCamelCase=6144,__lowerCamelCase=4,__lowerCamelCase=384,__lowerCamelCase=920,__lowerCamelCase=1E-5,__lowerCamelCase=0.3,__lowerCamelCase="relu",__lowerCamelCase=0.02,__lowerCamelCase=0.3,__lowerCamelCase=0.3,__lowerCamelCase=1,__lowerCamelCase=0,__lowerCamelCase=2,__lowerCamelCase=1,__lowerCamelCase=0.3,__lowerCamelCase=1,__lowerCamelCase=(7,),__lowerCamelCase=(3,),__lowerCamelCase=80,__lowerCamelCase=1,__lowerCamelCase=None,__lowerCamelCase="sum",__lowerCamelCase=False,**__lowerCamelCase,):
        super().__init__(**__lowerCamelCase,pad_token_id=__lowerCamelCase,bos_token_id=__lowerCamelCase,eos_token_id=__lowerCamelCase					)
        A__		   =		vocab_size
        A__		   =		hidden_size
        A__		   =		num_hidden_layers
        A__		   =		intermediate_size
        A__		   =		num_attention_heads
        A__		   =		attention_head_dim
        A__		   =		max_position_embeddings
        A__		   =		layer_norm_eps
        A__		   =		layerdrop
        A__		   =		hidden_act
        A__		   =		initializer_range
        A__		   =		hidden_dropout_prob
        A__		   =		attention_probs_dropout_prob
        A__		   =		pad_token_id
        A__		   =		bos_token_id
        A__		   =		eos_token_id
        A__		   =		conv_glu_dim
        A__		   =		conv_dropout
        A__		   =		num_conv_layers
        A__		   =		input_feat_per_channel
        A__		   =		input_channels
        A__		   =		conv_channels
        A__		   =		ctc_loss_reduction
        A__		   =		ctc_zero_infinity

        # prevents config testing fail with exporting to json
        A__		   =		list(__lowerCamelCase					)
        A__		   =		list(__lowerCamelCase					)

        if len(self.conv_kernel					) != self.num_conv_layers:
               raise ValueError(
                   '''Configuration for convolutional module is incorrect. '''
                   '''It is required that `len(config.conv_kernel)` == `config.num_conv_layers` '''
                   f"but is `len(config.conv_kernel) = {len(self.conv_kernel					)}`, "
                   f"`config.num_conv_layers = {self.num_conv_layers}`."					)












import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
    ' StableDiffusionInpaintPipeline` instead.'
)





