
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__							:							Optional[Any]									=			{
    "configuration_pegasus_x": ["PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP", "PegasusXConfig"],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__							:							Any									=			[
				    "PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "PegasusXForConditionalGeneration",
				    "PegasusXModel",
				    "PegasusXPreTrainedModel",
				]


if TYPE_CHECKING:
				from .configuration_pegasus_x import PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusXConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_pegasus_x import (
								    PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST,
								    PegasusXForConditionalGeneration,
								    PegasusXModel,
								    PegasusXPreTrainedModel,
								)


else:
				import sys

				lowercase__							:							Tuple									=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






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


lowercase__							:							Tuple									=			logging.get_logger(__name__)

lowercase__							:							Union[str, 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__    (							SCREAMING_SNAKE_CASE_    ):

							"""simple docstring"""






							_snake_case     		=  'mctct'



							def __init__(  self     ,	SCREAMING_SNAKE_CASE_=8065     ,	SCREAMING_SNAKE_CASE_=1536     ,	SCREAMING_SNAKE_CASE_=36     ,	SCREAMING_SNAKE_CASE_=6144     ,	SCREAMING_SNAKE_CASE_=4     ,	SCREAMING_SNAKE_CASE_=384     ,	SCREAMING_SNAKE_CASE_=920     ,	SCREAMING_SNAKE_CASE_=1E-5     ,	SCREAMING_SNAKE_CASE_=0.3     ,	SCREAMING_SNAKE_CASE_="relu"     ,	SCREAMING_SNAKE_CASE_=0.0_2     ,	SCREAMING_SNAKE_CASE_=0.3     ,	SCREAMING_SNAKE_CASE_=0.3     ,	SCREAMING_SNAKE_CASE_=1     ,	SCREAMING_SNAKE_CASE_=0     ,	SCREAMING_SNAKE_CASE_=2     ,	SCREAMING_SNAKE_CASE_=1     ,	SCREAMING_SNAKE_CASE_=0.3     ,	SCREAMING_SNAKE_CASE_=1     ,	SCREAMING_SNAKE_CASE_=(7,)     ,	SCREAMING_SNAKE_CASE_=(3,)     ,	SCREAMING_SNAKE_CASE_=80     ,	SCREAMING_SNAKE_CASE_=1     ,	SCREAMING_SNAKE_CASE_=None     ,	SCREAMING_SNAKE_CASE_="sum"     ,	SCREAMING_SNAKE_CASE_=False     ,	**SCREAMING_SNAKE_CASE_     ,	)->   Tuple:





													'''simple docstring'''






													super().__init__(**SCREAMING_SNAKE_CASE_     ,	pad_token_id=SCREAMING_SNAKE_CASE_     ,	bos_token_id=SCREAMING_SNAKE_CASE_     ,	eos_token_id=SCREAMING_SNAKE_CASE_			)
													__UpperCamelCase       =			vocab_size
													__UpperCamelCase       =			hidden_size
													__UpperCamelCase       =			num_hidden_layers
													__UpperCamelCase       =			intermediate_size
													__UpperCamelCase       =			num_attention_heads
													__UpperCamelCase       =			attention_head_dim
													__UpperCamelCase       =			max_position_embeddings
													__UpperCamelCase       =			layer_norm_eps
													__UpperCamelCase       =			layerdrop
													__UpperCamelCase       =			hidden_act
													__UpperCamelCase       =			initializer_range
													__UpperCamelCase       =			hidden_dropout_prob
													__UpperCamelCase       =			attention_probs_dropout_prob
													__UpperCamelCase       =			pad_token_id
													__UpperCamelCase       =			bos_token_id
													__UpperCamelCase       =			eos_token_id
													__UpperCamelCase       =			conv_glu_dim
													__UpperCamelCase       =			conv_dropout
													__UpperCamelCase       =			num_conv_layers
													__UpperCamelCase       =			input_feat_per_channel
													__UpperCamelCase       =			input_channels
													__UpperCamelCase       =			conv_channels
													__UpperCamelCase       =			ctc_loss_reduction
													__UpperCamelCase       =			ctc_zero_infinity

													# prevents config testing fail with exporting to json
													__UpperCamelCase       =			list(SCREAMING_SNAKE_CASE_			)
													__UpperCamelCase       =			list(SCREAMING_SNAKE_CASE_			)

													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}`."			)




