


import torch

from transformers import CamembertForMaskedLM, CamembertTokenizer



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_=5 )-> str:
				# Adapted from https://github.com/pytorch/fairseq/blob/master/fairseq/models/roberta/hub_interface.py
				assert masked_input.count('''<mask>''' ) == 1
				lowerCAmelCase_ :      Tuple    				=				torch.tensor(tokenizer.encode(lowerCAmelCase_ ,   add_special_tokens=lowerCAmelCase_ ) ).unsqueeze(0 )  # Batch size 1
				lowerCAmelCase_ :      str    				=				model(lowerCAmelCase_ )[0]  # The last hidden-state is the first element of the output tuple
				lowerCAmelCase_ :      Dict    				=				(input_ids.squeeze() == tokenizer.mask_token_id).nonzero().item()
				lowerCAmelCase_ :      str    				=				logits[0, masked_index, :]
				lowerCAmelCase_ :      Optional[int]    				=				logits.softmax(dim=0 )
				lowerCAmelCase_				,  lowerCAmelCase_ :      List[str]    				=				prob.topk(k=lowerCAmelCase_ ,   dim=0 )
				lowerCAmelCase_ :      Tuple    				=				''' '''.join(
				    [tokenizer.convert_ids_to_tokens(indices[i].item() ) for i in range(len(lowerCAmelCase_ ) )] )
				lowerCAmelCase_ :      Any    				=				tokenizer.mask_token
				lowerCAmelCase_ :      List[Any]    				=				[]
				for index, predicted_token_bpe in enumerate(topk_predicted_token_bpe.split(''' ''' ) ):
								lowerCAmelCase_ :      str    				=				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


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

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




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



from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_UpperCAmelCase			:  Tuple     =10



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )-> int:
				for i in range(lowerCAmelCase_ ,   lowerCAmelCase_ ):
								if array[i] == target:
												return i
				return -1



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ )-> int:
				lowerCAmelCase_ :      Any    				=				0
				lowerCAmelCase_ :      int    				=				len(lowerCAmelCase_ )
				while left <= right:
								if right - left < precision:
												return lin_search(lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )

								lowerCAmelCase_ :      List[Any]    				=				(left + right) // 3 + 1
								lowerCAmelCase_ :      List[str]    				=				2 * (left + right) // 3 + 1

								if array[one_third] == target:
												return one_third
								elif array[two_third] == target:
												return two_third

								elif target < array[one_third]:
												lowerCAmelCase_ :      Dict    				=				one_third - 1
								elif array[two_third] < target:
												lowerCAmelCase_ :      List[Any]    				=				two_third + 1

								else:
												lowerCAmelCase_ :      Union[str, Any]    				=				one_third + 1
												lowerCAmelCase_ :      Tuple    				=				two_third - 1
				else:
								return -1



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )-> int:
				if left < right:
								if right - left < precision:
												return lin_search(lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
								lowerCAmelCase_ :      Union[str, Any]    				=				(left + right) // 3 + 1
								lowerCAmelCase_ :      Optional[int]    				=				2 * (left + right) // 3 + 1

								if array[one_third] == target:
												return one_third
								elif array[two_third] == target:
												return two_third

								elif target < array[one_third]:
												return rec_ternary_search(lowerCAmelCase_ ,   one_third - 1 ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
								elif array[two_third] < target:
												return rec_ternary_search(two_third + 1 ,   lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
								else:
												return rec_ternary_search(one_third + 1 ,   two_third - 1 ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
				else:
								return -1


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						_UpperCAmelCase			:  Tuple     =input("""Enter numbers separated by comma:\n""").strip()
						_UpperCAmelCase			:  Union[str, Any]     =[int(item.strip()) for item in user_input.split(""",""")]
						assert collection == sorted(collection), f"List must be ordered.\n{collection}."
						_UpperCAmelCase			:  int     =int(input("""Enter the number to be found in the list:\n""").strip())
						_UpperCAmelCase			:  Optional[Any]     =ite_ternary_search(collection, target)
						_UpperCAmelCase			:  List[str]     =rec_ternary_search(0, len(collection) - 1, collection, target)
						if resulta != -1:
												print(f"""Iterative search: {target} found at positions: {resulta}""")
												print(f"""Recursive search: {target} found at positions: {resulta}""")
						else:
												print("""Not found""")