

"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__UpperCamelCase  :      Any							      =		logging.get_logger(__name__)

__UpperCamelCase  :      Any							      =		{
    '''xlm-roberta-base''': '''https://huggingface.co/xlm-roberta-base/resolve/main/config.json''',
    '''xlm-roberta-large''': '''https://huggingface.co/xlm-roberta-large/resolve/main/config.json''',
    '''xlm-roberta-large-finetuned-conll02-dutch''': (
        '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json'''
    ),
    '''xlm-roberta-large-finetuned-conll02-spanish''': (
        '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json'''
    ),
    '''xlm-roberta-large-finetuned-conll03-english''': (
        '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json'''
    ),
    '''xlm-roberta-large-finetuned-conll03-german''': (
        '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json'''
    ),
}







class 				SCREAMING_SNAKE_CASE					(		a_       ):






					"""simple docstring"""



					lowercase__				 =       "xlm-roberta"







					def __init__(       self			:				Tuple   ,lowercase_			:				Optional[int]=3_0_5_2_2   ,lowercase_			:				List[Any]=7_6_8   ,lowercase_			:				Optional[Any]=1_2   ,lowercase_			:				Dict=1_2   ,lowercase_			:				List[str]=3_0_7_2   ,lowercase_			:				Optional[int]="gelu"   ,lowercase_			:				Optional[Any]=0.1   ,lowercase_			:				Optional[Any]=0.1   ,lowercase_			:				List[Any]=5_1_2   ,lowercase_			:				List[str]=2   ,lowercase_			:				List[str]=0.02   ,lowercase_			:				List[str]=1E-12   ,lowercase_			:				List[str]=1   ,lowercase_			:				Optional[Any]=0   ,lowercase_			:				Any=2   ,lowercase_			:				Tuple="absolute"   ,lowercase_			:				Optional[int]=True   ,lowercase_			:				Optional[int]=None   ,**lowercase_			:				Tuple   ,):
						super().__init__(pad_token_id=lowercase_   ,bos_token_id=lowercase_   ,eos_token_id=lowercase_   ,**lowercase_		)

						lowerCAmelCase__	:						Union[str, Any]  				=	vocab_size
						lowerCAmelCase__	:						str  				=	hidden_size
						lowerCAmelCase__	:						int  				=	num_hidden_layers
						lowerCAmelCase__	:						Union[str, Any]  				=	num_attention_heads
						lowerCAmelCase__	:						Dict  				=	hidden_act
						lowerCAmelCase__	:						Any  				=	intermediate_size
						lowerCAmelCase__	:						int  				=	hidden_dropout_prob
						lowerCAmelCase__	:						Dict  				=	attention_probs_dropout_prob
						lowerCAmelCase__	:						Optional[Any]  				=	max_position_embeddings
						lowerCAmelCase__	:						List[Any]  				=	type_vocab_size
						lowerCAmelCase__	:						int  				=	initializer_range
						lowerCAmelCase__	:						Union[str, Any]  				=	layer_norm_eps
						lowerCAmelCase__	:						Tuple  				=	position_embedding_type
						lowerCAmelCase__	:						Any  				=	use_cache
						lowerCAmelCase__	:						int  				=	classifier_dropout







class 				SCREAMING_SNAKE_CASE					(		a_       ):






					"""simple docstring"""



					@property
					def        __lowerCAmelCase (       self			:				Any		):
						if self.task == "multiple-choice":
							lowerCAmelCase__	:						Optional[int]  				=	{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
						else:
							lowerCAmelCase__	:						List[str]  				=	{0: '''batch''', 1: '''sequence'''}
						return OrderedDict(
						    [
						        ('''input_ids''', dynamic_axis),
						        ('''attention_mask''', dynamic_axis),
						    ]		)







"""simple docstring"""





import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
__UpperCamelCase  :      Any							      =		logging.getLogger(__name__)

if __name__ == "__main__":
							__UpperCamelCase  :      Union[str, Any]							      =		argparse.ArgumentParser(
							    description='''Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)'''
							)
							parser.add_argument(
							    '''--data_file''', type=str, default='''data/dump.bert-base-uncased.pickle''', help='''The binarized dataset.'''
							)
							parser.add_argument(
							    '''--token_counts_dump''', type=str, default='''data/token_counts.bert-base-uncased.pickle''', help='''The dump file.'''
							)
							parser.add_argument('''--vocab_size''', default=3_0_5_2_2, type=int)
							__UpperCamelCase  :      Any							      =		parser.parse_args()

							logger.info(F'''Loading data from {args.data_file}''')
							with open(args.data_file, '''rb''') as fp:
														__UpperCamelCase  :      List[Any]							      =		pickle.load(fp)

							logger.info('''Counting occurrences for MLM.''')
							__UpperCamelCase  :      Dict							      =		Counter()
							for tk_ids in data:
														counter.update(tk_ids)
							__UpperCamelCase  :      Optional[Any]							      =		[0] * args.vocab_size
							for k, v in counter.items():
														__UpperCamelCase  :      Dict							      =		v

							logger.info(F'''Dump to {args.token_counts_dump}''')
							with open(args.token_counts_dump, '''wb''') as handle:
														pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)




