






'''simple docstring'''





import torch

from transformers import CamembertForMaskedLM, CamembertTokenizer


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


_a    :   Any        =			CamembertTokenizer.from_pretrained("""camembert-base""")
_a    :   Optional[Any]        =			CamembertForMaskedLM.from_pretrained("""camembert-base""")
model.eval()

_a    :   str        =			"""Le camembert est <mask> :)"""
print(fill_mask(masked_input, model, tokenizer, topk=3))











from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

_a    :   Optional[Any]        =			[
    """python""",
    """tqdm""",
    """regex""",
    """requests""",
    """packaging""",
    """filelock""",
    """numpy""",
    """tokenizers""",
    """huggingface-hub""",
    """safetensors""",
    """accelerate""",
    """pyyaml""",
]

for pkg in pkgs_to_check_at_runtime:
 if pkg in deps:
  if pkg == "tokenizers":
   # must be loaded here, or else tqdm check may fail
   from .utils import is_tokenizers_available

   if not is_tokenizers_available():
    continue  # not required, check version only if installed
  elif pkg == "accelerate":
   # must be loaded here, or else tqdm check may fail
   from .utils import is_accelerate_available

   # Maybe switch to is_torch_available in the future here so that Accelerate is hard dep of
   # Transformers with PyTorch
   if not is_accelerate_available():
    continue  # not required, check version only if installed

  require_version_core(deps[pkg])
 else:
  raise ValueError(f"""can't find {pkg} in {deps.keys()}, check dependency_versions_table.py""")


def 				snake_case__							(							UpperCAmelCase							:  Any    ,			UpperCAmelCase							:  Union[str, Any]=None       ):
    require_version(deps[pkg]    ,			UpperCAmelCase       )



