





'''simple docstring'''


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


_SCREAMING_SNAKE_CASE									=				logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE									=				{
    "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  lowerCAmelCase_		(		__magic_name__		):
 __lowerCamelCase    :				Any								=       "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      ,  )     ->				int:
     super().__init__(**_lowerCAmelCase      ,  pad_token_id=_lowerCAmelCase      ,  bos_token_id=_lowerCAmelCase      ,  eos_token_id=_lowerCAmelCase		)
     _lowerCAmelCase						      =   vocab_size
     _lowerCAmelCase						      =   hidden_size
     _lowerCAmelCase						      =   num_hidden_layers
     _lowerCAmelCase						      =   intermediate_size
     _lowerCAmelCase						      =   num_attention_heads
     _lowerCAmelCase						      =   attention_head_dim
     _lowerCAmelCase						      =   max_position_embeddings
     _lowerCAmelCase						      =   layer_norm_eps
     _lowerCAmelCase						      =   layerdrop
     _lowerCAmelCase						      =   hidden_act
     _lowerCAmelCase						      =   initializer_range
     _lowerCAmelCase						      =   hidden_dropout_prob
     _lowerCAmelCase						      =   attention_probs_dropout_prob
     _lowerCAmelCase						      =   pad_token_id
     _lowerCAmelCase						      =   bos_token_id
     _lowerCAmelCase						      =   eos_token_id
     _lowerCAmelCase						      =   conv_glu_dim
     _lowerCAmelCase						      =   conv_dropout
     _lowerCAmelCase						      =   num_conv_layers
     _lowerCAmelCase						      =   input_feat_per_channel
     _lowerCAmelCase						      =   input_channels
     _lowerCAmelCase						      =   conv_channels
     _lowerCAmelCase						      =   ctc_loss_reduction
     _lowerCAmelCase						      =   ctc_zero_infinity

     # prevents config testing fail with exporting to json
     _lowerCAmelCase						      =   list(_lowerCAmelCase		)
     _lowerCAmelCase						      =   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}`.'''		)









'''simple docstring'''


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


_SCREAMING_SNAKE_CASE									=				logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE									=				{
    "bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}

class  lowerCAmelCase_		(		__magic_name__		):
 __lowerCamelCase    :				str								=       "gpt_bigcode"
 __lowerCamelCase    :				Optional[int]								=       ["past_key_values"]
 __lowerCamelCase    :				List[str]								=       {
     "hidden_size": "n_embd",
     "max_position_embeddings": "n_positions",
     "num_attention_heads": "n_head",
     "num_hidden_layers": "n_layer",
 }




 def __init__(						self      ,  _lowerCAmelCase=50257      ,  _lowerCAmelCase=1024      ,  _lowerCAmelCase=768      ,  _lowerCAmelCase=12      ,  _lowerCAmelCase=12      ,  _lowerCAmelCase=None      ,  _lowerCAmelCase="gelu_pytorch_tanh"      ,  _lowerCAmelCase=0.1      ,  _lowerCAmelCase=0.1      ,  _lowerCAmelCase=0.1      ,  _lowerCAmelCase=1E-5      ,  _lowerCAmelCase=0.02      ,  _lowerCAmelCase=True      ,  _lowerCAmelCase=True      ,  _lowerCAmelCase=50256      ,  _lowerCAmelCase=50256      ,  _lowerCAmelCase=True      ,  _lowerCAmelCase=True      ,  _lowerCAmelCase=True      ,  **_lowerCAmelCase      ,  )     ->				List[Any]:
     _lowerCAmelCase						      =   vocab_size
     _lowerCAmelCase						      =   n_positions
     _lowerCAmelCase						      =   n_embd
     _lowerCAmelCase						      =   n_layer
     _lowerCAmelCase						      =   n_head
     _lowerCAmelCase						      =   n_inner
     _lowerCAmelCase						      =   activation_function
     _lowerCAmelCase						      =   resid_pdrop
     _lowerCAmelCase						      =   embd_pdrop
     _lowerCAmelCase						      =   attn_pdrop
     _lowerCAmelCase						      =   layer_norm_epsilon
     _lowerCAmelCase						      =   initializer_range
     _lowerCAmelCase						      =   scale_attn_weights
     _lowerCAmelCase						      =   use_cache
     _lowerCAmelCase						      =   attention_softmax_in_fpaa
     _lowerCAmelCase						      =   scale_attention_softmax_in_fpaa
     _lowerCAmelCase						      =   multi_query

     _lowerCAmelCase						      =   bos_token_id
     _lowerCAmelCase						      =   eos_token_id

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


