
'''simple docstring'''







import torch

from transformers import CamembertForMaskedLM, CamembertTokenizer
def  snake_case_		(    __SCREAMING_SNAKE_CASE :			Tuple				,				__SCREAMING_SNAKE_CASE :			Union[str, Any]				,				__SCREAMING_SNAKE_CASE :			List[str]				,				__SCREAMING_SNAKE_CASE :			List[str]=5							):



						"""simple docstring"""





						assert masked_input.count('''<mask>'''							) == 1
						lowercase_     :					str													=	torch.tensor(tokenizer.encode(__SCREAMING_SNAKE_CASE				,				add_special_tokens=__SCREAMING_SNAKE_CASE							)							).unsqueeze(0							)  # Batch size 1
						lowercase_     :					List[Any]													=	model(__SCREAMING_SNAKE_CASE							)[0]  # The last hidden-state is the first element of the output tuple
						lowercase_     :					Any													=	(input_ids.squeeze() == tokenizer.mask_token_id).nonzero().item()
						lowercase_     :					Optional[Any]													=	logits[0, masked_index, :]
						lowercase_     :					List[Any]													=	logits.softmax(dim=0							)
						lowercase_     :					int													=	prob.topk(k=__SCREAMING_SNAKE_CASE				,				dim=0							)
						lowercase_     :					List[str]													=	''' '''.join(
						    [tokenizer.convert_ids_to_tokens(indices[i].item()							) for i in range(len(__SCREAMING_SNAKE_CASE							)							)]							)
						lowercase_     :					Union[str, Any]													=	tokenizer.mask_token
						lowercase_     :					Union[str, Any]													=	[]
						for index, predicted_token_bpe in enumerate(topk_predicted_token_bpe.split(''' '''							)							):
												lowercase_     :					List[Any]													=	predicted_token_bpe.replace('''\u2581'''				,				''' '''							)
												if " {0}".format(__SCREAMING_SNAKE_CASE							) in masked_input:
																		topk_filled_outputs.append(
																		    (
																		        masked_input.replace(''' {0}'''.format(__SCREAMING_SNAKE_CASE							)				,				__SCREAMING_SNAKE_CASE							),
																		        values[index].item(),
																		        predicted_token,
																		    )							)
												else:
																		topk_filled_outputs.append(
																		    (
																		        masked_input.replace(__SCREAMING_SNAKE_CASE				,				__SCREAMING_SNAKE_CASE							),
																		        values[index].item(),
																		        predicted_token,
																		    )							)
						return topk_filled_outputs


_lowercase			:  Union[str, Any]   							=	CamembertTokenizer.from_pretrained("camembert-base")
_lowercase			:  Tuple   							=	CamembertForMaskedLM.from_pretrained("camembert-base")
model.eval()

_lowercase			:  List[Any]   							=	"Le camembert est <mask> :)"




print(fill_mask(masked_input, model, tokenizer, topk=3))



'''simple docstring'''







def  snake_case_		(    __SCREAMING_SNAKE_CASE :			str							):



						"""simple docstring"""





						return [
						    txt[:a] + txt[a].upper() + txt[a + 1 :]
						    for a in range(len(__SCREAMING_SNAKE_CASE							)							)
						    if txt[a].isalpha()
						]


if __name__ == "__main__":
							__import__("doctest").testmod()



