


'''simple docstring'''






import inspect
import warnings
from typing import Any, Dict, Optional, Union

from packaging import version


def  _snake_case       (					*A			,   A = None			,   A=True			,   A=2	)						->   Optional[Any]:
							from .. import __version__

							lowerCAmelCase__	       =     take_from
							lowerCAmelCase__	       =     ()
							if not isinstance(args[0]			,   A	):
														lowerCAmelCase__	       =     (args,)

							for attribute, version_name, message in args:
														if version.parse(version.parse(A	).base_version	) >= version.parse(A	):
																					raise ValueError(
																					    F"""The deprecation tuple {(attribute, version_name, message)} should be removed since diffusers'"""
																					    F""" version {__version__} is >= {version_name}"""	)

														lowerCAmelCase__	       =     None
														if isinstance(A			,   A	) and attribute in deprecated_kwargs:
																					values += (deprecated_kwargs.pop(A	),)
																					lowerCAmelCase__	       =     F"""The `{attribute}` argument is deprecated and will be removed in version {version_name}."""
														elif hasattr(A			,   A	):
																					values += (getattr(A			,   A	),)
																					lowerCAmelCase__	       =     F"""The `{attribute}` attribute is deprecated and will be removed in version {version_name}."""
														elif deprecated_kwargs is None:
																					lowerCAmelCase__	       =     F"""`{attribute}` is deprecated and will be removed in version {version_name}."""

														if warning is not None:
																					lowerCAmelCase__	       =     warning + ''' ''' if standard_warn else ''''''
																					warnings.warn(warning + message			,   A			,   stacklevel=A	)

							if isinstance(A			,   A	) and len(A	) > 0:
														lowerCAmelCase__	       =     inspect.getouterframes(inspect.currentframe()	)[1]
														lowerCAmelCase__	       =     call_frame.filename
														lowerCAmelCase__	       =     call_frame.lineno
														lowerCAmelCase__	       =     call_frame.function
														lowerCAmelCase__       , lowerCAmelCase__	       =     next(iter(deprecated_kwargs.items()	)	)
														raise TypeError(F"""{function} in {filename} line {line_number-1} got an unexpected keyword argument `{key}`"""	)

							if len(A	) == 0:
														return
							elif len(A	) == 1:
														return values[0]
							return values



'''simple docstring'''






import torch

from transformers import CamembertForMaskedLM, CamembertTokenizer


def  _snake_case       (					A			,   A			,   A			,   A=5	)						->   List[str]:
							# Adapted from https://github.com/pytorch/fairseq/blob/master/fairseq/models/roberta/hub_interface.py
							assert masked_input.count('''<mask>'''	) == 1
							lowerCAmelCase__	       =     torch.tensor(tokenizer.encode(A			,   add_special_tokens=A	)	).unsqueeze(0	)  # Batch size 1
							lowerCAmelCase__	       =     model(A	)[0]  # The last hidden-state is the first element of the output tuple
							lowerCAmelCase__	       =     (input_ids.squeeze() == tokenizer.mask_token_id).nonzero().item()
							lowerCAmelCase__	       =     logits[0, masked_index, :]
							lowerCAmelCase__	       =     logits.softmax(dim=0	)
							lowerCAmelCase__       , lowerCAmelCase__	       =     prob.topk(k=A			,   dim=0	)
							lowerCAmelCase__	       =     ''' '''.join(
							    [tokenizer.convert_ids_to_tokens(indices[i].item()	) for i in range(len(A	)	)]	)
							lowerCAmelCase__	       =     tokenizer.mask_token
							lowerCAmelCase__	       =     []
							for index, predicted_token_bpe in enumerate(topk_predicted_token_bpe.split(''' '''	)	):
														lowerCAmelCase__	       =     predicted_token_bpe.replace('''\u2581'''			,   ''' '''	)
														if " {0}".format(A	) in masked_input:
																					topk_filled_outputs.append(
																					    (
																					        masked_input.replace(''' {0}'''.format(A	)			,   A	),
																					        values[index].item(),
																					        predicted_token,
																					    )	)
														else:
																					topk_filled_outputs.append(
																					    (
																					        masked_input.replace(A			,   A	),
																					        values[index].item(),
																					        predicted_token,
																					    )	)
							return topk_filled_outputs


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

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






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