
import torch

from transformers import CamembertForMaskedLM, CamembertTokenizer


def 							__A(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase=5 )		->				Any:

		"""simple docstring"""






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


lowerCamelCase__	=							CamembertTokenizer.from_pretrained("camembert-base")
lowerCamelCase__	=							CamembertForMaskedLM.from_pretrained("camembert-base")
model.eval()

lowerCamelCase__	=							"Le camembert est <mask> :)"







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





lowerCamelCase__	=							[
    "DownloadConfig",
    "DownloadManager",
    "DownloadMode",
    "StreamingDownloadManager",
]

from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager



