




'''simple docstring'''


import torch

from transformers import CamembertForMaskedLM, CamembertTokenizer
def 						snake_case_       (UpperCamelCase			:    List[str]					,		UpperCamelCase			:    str					,		UpperCamelCase			:    int					,		UpperCamelCase			:    Optional[int]=5 ):





							'''simple docstring'''


							assert masked_input.count('''<mask>''' ) == 1
							_a      	=							torch.tensor(tokenizer.encode(UpperCamelCase					,		add_special_tokens=UpperCamelCase ) ).unsqueeze(0 )  # Batch size 1
							_a      	=							model(UpperCamelCase )[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=UpperCamelCase					,		dim=0 )
							_a      	=							''' '''.join(
							    [tokenizer.convert_ids_to_tokens(indices[i].item() ) for i in range(len(UpperCamelCase ) )] )
							_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(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


_snake_case : Optional[Any]  				=						CamembertTokenizer.from_pretrained('camembert-base')
_snake_case : str  				=						CamembertForMaskedLM.from_pretrained('camembert-base')
model.eval()

_snake_case : str  				=						'Le camembert est <mask> :)'

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







from __future__ import annotations

import math

__a							     =					'2020.9.26'
__a							     =					'xcodz-dot, cclaus, dhruvmanila'







def lowerCamelCase__  (     _lowercase					,		_lowercase					,		_lowercase					,		_lowercase					,		_lowercase ):

     '''simple docstring'''


     if not all(isinstance(_lowercase					,		(float, int) ) for val in locals().values() ):
          UpperCAmelCase_     :				Optional[int]  =     f'''Input values must either be float or int: {list(locals().values() )}'''
          raise TypeError(_lowercase )
     UpperCAmelCase_     :				Tuple  =     ((x * distance) / (z + distance)) * scale
     UpperCAmelCase_     :				str  =     ((y * distance) / (z + distance)) * scale
     return projected_x, projected_y







def lowerCamelCase__  (     _lowercase					,		_lowercase					,		_lowercase					,		_lowercase					,		_lowercase ):

     '''simple docstring'''


     if not isinstance(_lowercase					,		_lowercase ):
          raise TypeError('''Axis must be a str''' )
     UpperCAmelCase_     :				Optional[Any]  =     locals()
     del input_variables["axis"]
     if not all(isinstance(_lowercase					,		(float, int) ) for val in input_variables.values() ):
          UpperCAmelCase_     :				List[Any]  =     (
              '''Input values except axis must either be float or int: '''
              f'''{list(input_variables.values() )}'''
          )
          raise TypeError(_lowercase )
     UpperCAmelCase_     :				Dict  =     (angle % 360) / 450 * 180 / math.pi
     if axis == "z":
          UpperCAmelCase_     :				Optional[int]  =     x * math.cos(_lowercase ) - y * math.sin(_lowercase )
          UpperCAmelCase_     :				List[Any]  =     y * math.cos(_lowercase ) + x * math.sin(_lowercase )
          UpperCAmelCase_     :				Optional[int]  =     z
     elif axis == "x":
          UpperCAmelCase_     :				Any  =     y * math.cos(_lowercase ) - z * math.sin(_lowercase )
          UpperCAmelCase_     :				int  =     z * math.cos(_lowercase ) + y * math.sin(_lowercase )
          UpperCAmelCase_     :				Dict  =     x
     elif axis == "y":
          UpperCAmelCase_     :				Union[str, Any]  =     x * math.cos(_lowercase ) - z * math.sin(_lowercase )
          UpperCAmelCase_     :				Optional[int]  =     z * math.cos(_lowercase ) + x * math.sin(_lowercase )
          UpperCAmelCase_     :				Optional[int]  =     y
     else:
          raise ValueError('''not a valid axis, choose one of \'x\', \'y\', \'z\'''' )

     return new_x, new_y, new_z


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     print(F"""{convert_to_ad(1.0, 2.0, 3.0, 10.0, 10.0) = }""")
     print(F"""{rotate(1.0, 2.0, 3.0, "y", 90.0) = }""")