
"""simple docstring"""




import copy

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


__lowerCAmelCase							:  List[Any] 				=		logging.get_logger(__name__)

__lowerCAmelCase							:  List[Any] 				=		{}
class SCREAMING_SNAKE_CASE       (      lowerCAmelCase					):






	'''simple docstring'''







	snake_case__							:		Dict         =		'fsmt_decoder'


	def __init__(  self :Dict       ,    __magic_name__ :Tuple=0       ,    __magic_name__ :List[Any]=0			)			->   Dict:

			'''simple docstring'''






			super().__init__()
			a__   		=     vocab_size
			a__   		=     bos_token_id

class SCREAMING_SNAKE_CASE       (      lowerCAmelCase					):






	'''simple docstring'''







	snake_case__							:		int         =		'fsmt'
	snake_case__							:		Dict         =		{'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}


	def __init__(  self :str       ,    __magic_name__ :Dict=["en", "de"]       ,    __magic_name__ :Tuple=42024       ,    __magic_name__ :Optional[int]=42024       ,    __magic_name__ :str="relu"       ,    __magic_name__ :int=1024       ,    __magic_name__ :List[str]=200       ,    __magic_name__ :List[str]=1024       ,    __magic_name__ :Union[str, Any]=4096       ,    __magic_name__ :int=12       ,    __magic_name__ :Union[str, Any]=16       ,    __magic_name__ :List[str]=0.0       ,    __magic_name__ :Any=4096       ,    __magic_name__ :Union[str, Any]=12       ,    __magic_name__ :str=16       ,    __magic_name__ :int=0.0       ,    __magic_name__ :List[Any]=0.0       ,    __magic_name__ :int=0.1       ,    __magic_name__ :List[str]=0.0       ,    __magic_name__ :Union[str, Any]=0.02       ,    __magic_name__ :Dict=2       ,    __magic_name__ :Optional[int]=True       ,    __magic_name__ :List[str]=True       ,    __magic_name__ :Dict=False       ,    __magic_name__ :Union[str, Any]=5       ,    __magic_name__ :List[str]=1.0       ,    __magic_name__ :Optional[int]=False       ,    __magic_name__ :Optional[int]=True       ,    __magic_name__ :Union[str, Any]=1       ,    __magic_name__ :int=0       ,    __magic_name__ :List[Any]=2       ,    __magic_name__ :List[Any]=2       ,    **__magic_name__ :Any       ,    )			->   str:

			'''simple docstring'''






			a__   		=     langs
			a__   		=     src_vocab_size
			a__   		=     tgt_vocab_size
			a__   		=     d_model  # encoder_embed_dim and decoder_embed_dim

			a__   		=     encoder_ffn_dim
			a__   		=     a__   		=     encoder_layers
			a__   		=     encoder_attention_heads
			a__   		=     encoder_layerdrop
			a__   		=     decoder_layerdrop
			a__   		=     decoder_ffn_dim
			a__   		=     decoder_layers
			a__   		=     decoder_attention_heads
			a__   		=     max_position_embeddings
			a__   		=     init_std  # Normal(0, this parameter)
			a__   		=     activation_function

			a__   		=     DecoderConfig(vocab_size=__magic_name__       ,    bos_token_id=__magic_name__			)
			if "decoder" in common_kwargs:
					del common_kwargs["decoder"]

			a__   		=     scale_embedding  # scale factor will be sqrt(d_model) if True

			# 3 Types of Dropout
			a__   		=     attention_dropout
			a__   		=     activation_dropout
			a__   		=     dropout

			a__   		=     use_cache
			super().__init__(
			    pad_token_id=__magic_name__       ,    bos_token_id=__magic_name__       ,    eos_token_id=__magic_name__       ,    decoder_start_token_id=__magic_name__       ,    is_encoder_decoder=__magic_name__       ,    tie_word_embeddings=__magic_name__       ,    forced_eos_token_id=__magic_name__       ,    max_length=__magic_name__       ,    num_beams=__magic_name__       ,    length_penalty=__magic_name__       ,    early_stopping=__magic_name__       ,    **__magic_name__       ,    )






	def    _UpperCamelCase							(  self :int			)			->   Union[str, Any]:

			'''simple docstring'''






			a__   		=     copy.deepcopy(self.__dict__			)
			a__   		=     self.decoder.to_dict()
			a__   		=     self.__class__.model_type
			return output






"""simple docstring"""




import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

__lowerCAmelCase							:  Dict 				=		logging.getLogger()

def __snake_case (      )       ->    Optional[int]:


		"""simple docstring"""





		a__   		=     argparse.ArgumentParser()
		parser.add_argument('''-f'''    )
		a__   		=     parser.parse_args()
		return args.f




class SCREAMING_SNAKE_CASE       (      lowerCAmelCase					):






	'''simple docstring'''







	def    _UpperCamelCase							(  self :Tuple			)			->   Union[str, Any]:

			'''simple docstring'''






			a__   		=     logging.StreamHandler(sys.stdout			)
			logger.addHandler(__magic_name__			)

			a__   		=     self.get_auto_remove_tmp_dir()
			a__   		=     F"\n            run_glue_with_pabee.py\n            --model_type albert\n            --model_name_or_path albert-base-v2\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --task_name mrpc\n            --do_train\n            --do_eval\n            --per_gpu_train_batch_size=2\n            --per_gpu_eval_batch_size=1\n            --learning_rate=2e-5\n            --max_steps=50\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            ".split()

			with patch.object(__magic_name__       ,    '''argv'''       ,    __magic_name__			):
					a__   		=     run_glue_with_pabee.main()
					for value in result.values():
							self.assertGreaterEqual(__magic_name__       ,    0.75			)




