



'''simple docstring'''


from typing import List

from .keymap import KEYMAP, get_character






def  UpperCAmelCase_       (		lowercase__       ):


     '''simple docstring'''







     def decorator(lowercase__       ):
          a_       		=getattr(lowercase__       ,	"handle_key"       ,	[]       )
          handle += [key]
          setattr(lowercase__       ,	"handle_key"       ,	lowercase__       )
          return func

     return decorator






def  UpperCAmelCase_       (		*lowercase__       ):


     '''simple docstring'''







     def decorator(lowercase__       ):
          a_       		=getattr(lowercase__       ,	"handle_key"       ,	[]       )
          handle += keys
          setattr(lowercase__       ,	"handle_key"       ,	lowercase__       )
          return func

     return decorator







class 	UpperCAmelCase	(		__a):


 '''simple docstring'''




 def __new__(   cls							,  lowerCAmelCase_							,  lowerCAmelCase_							,  lowerCAmelCase_) ->      Optional[int]:



      """simple docstring"""







      a_       		=super().__new__(cls							,  lowerCAmelCase_							,  lowerCAmelCase_							,  lowerCAmelCase_)
      if not hasattr(lowerCAmelCase_							,  "key_handler"):
           setattr(lowerCAmelCase_							,  "key_handler"							,  {})
      setattr(lowerCAmelCase_							,  "handle_input"							,  KeyHandler.handle_input)

      for value in attrs.values():
           a_       		=getattr(lowerCAmelCase_							,  "handle_key"							,  [])
           for key in handled_keys:
                a_       		=value
      return new_cls




 @staticmethod
 def       lowercase_  (   cls) ->      Optional[int]:



      """simple docstring"""







      a_       		=get_character()
      if char != KEYMAP["undefined"]:
           a_       		=ord(lowerCAmelCase_)
      a_       		=cls.key_handler.get(lowerCAmelCase_)
      if handler:
           a_       		=char
           return handler(cls)
      else:
           return None






def  UpperCAmelCase_       (		cls       ):


     '''simple docstring'''







     return KeyHandler(cls.__name__       ,	cls.__bases__       ,	cls.__dict__.copy()       )







'''simple docstring'''


import torch

from transformers import CamembertForMaskedLM, CamembertTokenizer






def  UpperCAmelCase_       (		lowercase__       ,	lowercase__       ,	lowercase__       ,	lowercase__=5       ):


     '''simple docstring'''







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


lowercase							       =			CamembertTokenizer.from_pretrained('''camembert-base''')
lowercase							       =			CamembertForMaskedLM.from_pretrained('''camembert-base''')
model.eval()

lowercase							       =			'''Le camembert est <mask> :)'''

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


