"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

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


_a     :     Any= logging.get_logger(__name__)

_a     :     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 		UpperCamelCase			(    a_						):
				UpperCAmelCase				:      Tuple    =		"""xlm-roberta"""



				def __init__(self				:      Tuple	,  _A				:      Optional[int]=3_05_22	,  _A				:      List[Any]=7_68	,  _A				:      Optional[Any]=12	,  _A				:      Dict=12	,  _A				:      List[str]=30_72	,  _A				:      Optional[int]="gelu"	,  _A				:      Optional[Any]=0.1	,  _A				:      Optional[Any]=0.1	,  _A				:      List[Any]=5_12	,  _A				:      List[str]=2	,  _A				:      List[str]=0.02	,  _A				:      List[str]=1E-12	,  _A				:      List[str]=1	,  _A				:      Optional[Any]=0	,  _A				:      Any=2	,  _A				:      Tuple="absolute"	,  _A				:      Optional[int]=True	,  _A				:      Optional[int]=None	,  **_A				:      Tuple	,  )    ->	Any:
					super().__init__(pad_token_id=lowercase_	,  bos_token_id=lowercase_	,  eos_token_id=lowercase_	,  **lowercase_)

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







class 		UpperCamelCase			(    a_						):



				@property
				def 					_lowercase     (self				:      Any)    ->	Union[str, Any]:
					if self.task == "multiple-choice":
						__snake_case			:							Optional[int]      		= {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
					else:
						__snake_case			:							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)




