



'''simple docstring'''

import argparse
from collections import defaultdict






def       __lowercase  (_SCREAMING_SNAKE_CASE      :Any    ,	_SCREAMING_SNAKE_CASE      :Optional[Any]    ,	_SCREAMING_SNAKE_CASE      :Tuple    ,	_SCREAMING_SNAKE_CASE      :Union[str, Any]    ,	_SCREAMING_SNAKE_CASE      :Dict       ):
				SCREAMING_SNAKE_CASE  :						Optional[int]      					= F'''{file}_{class_name}_{test_name}'''
				done_test[_id] += 1

				with open(_lowercase    ,	'''r'''       ) as f:
								SCREAMING_SNAKE_CASE  :						Optional[int]      					= f.readlines()

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

				SCREAMING_SNAKE_CASE  :						Optional[int]      					= []
				for line in lines:
								if line.startswith(_lowercase       ):
												SCREAMING_SNAKE_CASE  :						int      					= True
								elif in_class and line.startswith(_lowercase       ):
												SCREAMING_SNAKE_CASE  :						List[Any]      					= True
								elif in_class and in_func and (line.startswith(_lowercase       ) or line.startswith(_lowercase       )):
												SCREAMING_SNAKE_CASE  :						str      					= len(line.split(correct_line.split()[0]       )[0]       )
												count += 1

												if count == done_test[_id]:
																SCREAMING_SNAKE_CASE  :						List[Any]      					= 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  :						Any      					= False
								else:
												new_lines.append(_lowercase       )

				with open(_lowercase    ,	'''w'''       ) as f:
								for line in new_lines:
												f.write(_lowercase       )






def       __lowercase  (_SCREAMING_SNAKE_CASE      :Dict    ,	_SCREAMING_SNAKE_CASE      :List[Any]=None       ):
				if fail is not None:
								with open(_lowercase    ,	'''r'''       ) as f:
												SCREAMING_SNAKE_CASE  :						Any      					= {l.strip() for l in f.readlines()}
				else:
								SCREAMING_SNAKE_CASE  :						str      					= None

				with open(_lowercase    ,	'''r'''       ) as f:
								SCREAMING_SNAKE_CASE  :						str      					= f.readlines()

				SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= defaultdict(_lowercase       )
				for line in correct_lines:
								SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= line.split(''';'''       )
								if test_failures is None or "::".join([file, class_name, test_name]       ) in test_failures:
												overwrite_file(_lowercase    ,	_lowercase    ,	_lowercase    ,	_lowercase    ,	_lowercase       )


if __name__ == "__main__":
	snake_case_			=     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)
	snake_case_			=     parser.parse_args()

	main(args.correct_filename, args.fail_filename)









'''simple docstring'''

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


snake_case_			=     logging.get_logger(__name__)

snake_case_			=     {
    """facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}


class 	a__     (				_lowercase	):
	__magic_name__		:    Optional[Any]	    =     "nllb-moe"
	__magic_name__		:    Optional[Any]	    =     ["past_key_values"]
	__magic_name__		:    Optional[int]	    =     {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}


	def __init__(self : int,					__UpperCAmelCase : Tuple=128112,					__UpperCAmelCase : Any=1024,					__UpperCAmelCase : Optional[Any]=12,					__UpperCAmelCase : Optional[int]=4096,					__UpperCAmelCase : Any=16,					__UpperCAmelCase : Any=12,					__UpperCAmelCase : Optional[Any]=4096,					__UpperCAmelCase : Optional[int]=16,					__UpperCAmelCase : List[Any]=0.05,					__UpperCAmelCase : Dict=0.05,					__UpperCAmelCase : Dict=True,					__UpperCAmelCase : List[Any]=True,					__UpperCAmelCase : Any="relu",					__UpperCAmelCase : Union[str, Any]=1024,					__UpperCAmelCase : Optional[int]=0.1,					__UpperCAmelCase : Tuple=0.1,					__UpperCAmelCase : List[Any]=0.0,					__UpperCAmelCase : Optional[int]=0.02,					__UpperCAmelCase : Tuple=2,					__UpperCAmelCase : int=True,					__UpperCAmelCase : int=False,					__UpperCAmelCase : int="float32",					__UpperCAmelCase : Optional[Any]=False,					__UpperCAmelCase : List[str]=128,					__UpperCAmelCase : Dict=64,					__UpperCAmelCase : Dict=4,					__UpperCAmelCase : Optional[Any]=4,					__UpperCAmelCase : Optional[Any]=0.001,					__UpperCAmelCase : Optional[Any]=0.001,					__UpperCAmelCase : Optional[Any]="all",					__UpperCAmelCase : List[str]=False,					__UpperCAmelCase : Dict=False,					__UpperCAmelCase : Any=1.0,					__UpperCAmelCase : Dict=0.2,					__UpperCAmelCase : int=1,					__UpperCAmelCase : Union[str, Any]=0,					__UpperCAmelCase : Any=2,					__UpperCAmelCase : Union[str, Any]=False,					**__UpperCAmelCase : Dict,					)     ->			List[Any]:

					"""simple docstring"""

					SCREAMING_SNAKE_CASE  :						Any      					= vocab_size
					SCREAMING_SNAKE_CASE  :						int      					= max_position_embeddings
					SCREAMING_SNAKE_CASE  :						Optional[int]      					= d_model
					SCREAMING_SNAKE_CASE  :						Dict      					= encoder_ffn_dim
					SCREAMING_SNAKE_CASE  :						int      					= encoder_layers
					SCREAMING_SNAKE_CASE  :						str      					= encoder_attention_heads
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= decoder_ffn_dim
					SCREAMING_SNAKE_CASE  :						str      					= decoder_layers
					SCREAMING_SNAKE_CASE  :						Dict      					= decoder_attention_heads
					SCREAMING_SNAKE_CASE  :						Dict      					= dropout
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= attention_dropout
					SCREAMING_SNAKE_CASE  :						Dict      					= activation_dropout
					SCREAMING_SNAKE_CASE  :						List[str]      					= activation_function
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= init_std
					SCREAMING_SNAKE_CASE  :						Any      					= encoder_layerdrop
					SCREAMING_SNAKE_CASE  :						Optional[int]      					= decoder_layerdrop
					SCREAMING_SNAKE_CASE  :						Dict      					= use_cache
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= encoder_layers
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= scale_embedding  # scale factor will be sqrt(d_model) if True
					SCREAMING_SNAKE_CASE  :						List[str]      					= router_z_loss_coef
					SCREAMING_SNAKE_CASE  :						List[str]      					= router_aux_loss_coef
					SCREAMING_SNAKE_CASE  :						int      					= decoder_sparse_step
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= encoder_sparse_step
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= num_experts
					SCREAMING_SNAKE_CASE  :						List[Any]      					= expert_capacity
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= router_bias
					if router_dtype not in ["float32", "float16", "bfloat16"]:
									raise ValueError(F'''`router_dtype` must be one of \'float32\', \'float16\' or \'bfloat16\', got {router_dtype}'''      )
					SCREAMING_SNAKE_CASE  :						Union[str, Any]      					= router_dtype

					SCREAMING_SNAKE_CASE  :						int      					= router_ignore_padding_tokens
					SCREAMING_SNAKE_CASE  :						Dict      					= batch_prioritized_routing
					SCREAMING_SNAKE_CASE  :						Dict      					= second_expert_policy
					SCREAMING_SNAKE_CASE  :						Tuple      					= normalize_router_prob_before_dropping
					SCREAMING_SNAKE_CASE  :						List[str]      					= moe_eval_capacity_token_fraction
					SCREAMING_SNAKE_CASE  :						List[Any]      					= moe_token_dropout
					SCREAMING_SNAKE_CASE  :						List[Any]      					= output_router_logits
					super().__init__(
					    pad_token_id=__UpperCAmelCase,					bos_token_id=__UpperCAmelCase,					eos_token_id=__UpperCAmelCase,					is_encoder_decoder=__UpperCAmelCase,					decoder_start_token_id=__UpperCAmelCase,					**__UpperCAmelCase,					)




