"""simple docstring"""





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


lowerCAmelCase_     =	logging.get_logger(__name__)

lowerCAmelCase_     =	{
    '''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  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						"mctct"





				def __init__(      self							:							int      ,    _A							:							List[Any]=8_0_6_5      ,    _A							:							Dict=1_5_3_6      ,    _A							:							Dict=3_6      ,    _A							:							Union[str, Any]=6_1_4_4      ,    _A							:							List[Any]=4      ,    _A							:							Optional[Any]=3_8_4      ,    _A							:							List[Any]=9_2_0      ,    _A							:							Union[str, Any]=1e-5      ,    _A							:							int=0.3      ,    _A							:							List[str]="relu"      ,    _A							:							str=0.02      ,    _A							:							List[Any]=0.3      ,    _A							:							Tuple=0.3      ,    _A							:							List[str]=1      ,    _A							:							Any=0      ,    _A							:							Dict=2      ,    _A							:							Optional[int]=1      ,    _A							:							Optional[Any]=0.3      ,    _A							:							Union[str, Any]=1      ,    _A							:							Dict=(7,)      ,    _A							:							Optional[int]=(3,)      ,    _A							:							Optional[int]=8_0      ,    _A							:							Tuple=1      ,    _A							:							Optional[Any]=None      ,    _A							:							Optional[Any]="sum"      ,    _A							:							Optional[Any]=False      ,    **_A							:							List[str]      ,    ):



											"""simple docstring"""







											super().__init__(**_A      ,    pad_token_id=_A      ,    bos_token_id=_A      ,    eos_token_id=_A)
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    vocab_size
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    hidden_size
											_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    num_hidden_layers
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    intermediate_size
											_SCREAMING_SNAKE_CASE		:						Any			  =    num_attention_heads
											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    attention_head_dim
											_SCREAMING_SNAKE_CASE		:						str			  =    max_position_embeddings
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    layer_norm_eps
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    layerdrop
											_SCREAMING_SNAKE_CASE		:						str			  =    hidden_act
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    initializer_range
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    hidden_dropout_prob
											_SCREAMING_SNAKE_CASE		:						Any			  =    attention_probs_dropout_prob
											_SCREAMING_SNAKE_CASE		:						Dict			  =    pad_token_id
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    bos_token_id
											_SCREAMING_SNAKE_CASE		:						int			  =    eos_token_id
											_SCREAMING_SNAKE_CASE		:						Tuple			  =    conv_glu_dim
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    conv_dropout
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    num_conv_layers
											_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    input_feat_per_channel
											_SCREAMING_SNAKE_CASE		:						int			  =    input_channels
											_SCREAMING_SNAKE_CASE		:						Tuple			  =    conv_channels
											_SCREAMING_SNAKE_CASE		:						Dict			  =    ctc_loss_reduction
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    ctc_zero_infinity

											# prevents config testing fail with exporting to json
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    list(_A)
											_SCREAMING_SNAKE_CASE		:						Any			  =    list(_A)

											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"""





import argparse
from collections import defaultdict



def      lowerCamelCase_(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE  )->    int:
							_SCREAMING_SNAKE_CASE		:						str			  =    F"""{file}_{class_name}_{test_name}"""
							done_test[_id] += 1

							with open(__SCREAMING_SNAKE_CASE     ,	"""r"""  ) as f:
														_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    f.readlines()

							_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    F"""class {class_name}("""
							_SCREAMING_SNAKE_CASE		:						List[Any]			  =    F"""{4 * " "}def {test_name}("""
							_SCREAMING_SNAKE_CASE		:						Tuple			  =    F"""{8 * " "}{correct_line.split()[0]}"""
							_SCREAMING_SNAKE_CASE		:						List[Any]			  =    F"""{16 * " "}{correct_line.split()[0]}"""
							_SCREAMING_SNAKE_CASE		:						List[str]			  =    False
							_SCREAMING_SNAKE_CASE		:						Tuple			  =    False
							_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    False
							_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    False
							_SCREAMING_SNAKE_CASE		:						Any			  =    0
							_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    0

							_SCREAMING_SNAKE_CASE		:						Dict			  =    []
							for line in lines:
														if line.startswith(__SCREAMING_SNAKE_CASE  ):
																					_SCREAMING_SNAKE_CASE		:						Any			  =    True
														elif in_class and line.startswith(__SCREAMING_SNAKE_CASE  ):
																					_SCREAMING_SNAKE_CASE		:						str			  =    True
														elif in_class and in_func and (line.startswith(__SCREAMING_SNAKE_CASE  ) or line.startswith(__SCREAMING_SNAKE_CASE  )):
																					_SCREAMING_SNAKE_CASE		:						Dict			  =    len(line.split(correct_line.split()[0]  )[0]  )
																					count += 1

																					if count == done_test[_id]:
																												_SCREAMING_SNAKE_CASE		:						int			  =    True

														if in_class and in_func and in_line:
																					if ")" not in line:
																												continue
																					else:
																												_SCREAMING_SNAKE_CASE		:						Any			  =    True

														if in_class and in_func and in_line and insert_line:
																					new_lines.append(F"""{spaces * " "}{correct_line}"""  )
																					_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    False
														else:
																					new_lines.append(__SCREAMING_SNAKE_CASE  )

							with open(__SCREAMING_SNAKE_CASE     ,	"""w"""  ) as f:
														for line in new_lines:
																					f.write(__SCREAMING_SNAKE_CASE  )



def      lowerCamelCase_(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE=None  )->    Optional[Any]:
							if fail is not None:
														with open(__SCREAMING_SNAKE_CASE     ,	"""r"""  ) as f:
																					_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    {l.strip() for l in f.readlines()}
							else:
														_SCREAMING_SNAKE_CASE		:						str			  =    None

							with open(__SCREAMING_SNAKE_CASE     ,	"""r"""  ) as f:
														_SCREAMING_SNAKE_CASE		:						str			  =    f.readlines()

							_SCREAMING_SNAKE_CASE		:						str			  =    defaultdict(__SCREAMING_SNAKE_CASE  )
							for line in correct_lines:
														_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    line.split(""";"""  )
														if test_failures is None or "::".join([file, class_name, test_name]  ) in test_failures:
																					overwrite_file(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE  )


if __name__ == "__main__":
			lowerCAmelCase_     =	argparse.ArgumentParser()
			parser.add_argument('''--correct_filename''', help='''filename of tests with expected result''')
			parser.add_argument('''--fail_filename''', help='''filename of test failures''', type=str, default=None)
			lowerCAmelCase_     =	parser.parse_args()

			main(args.correct_filename, args.fail_filename)


