





'''simple docstring'''


from __future__ import annotations

import math

a__			:					int       						=						'2020.9.26'
a__			:					Optional[Any]       						=						'xcodz-dot, cclaus, dhruvmanila'
def       __snake_case		( SCREAMING_SNAKE_CASE_ :			float			,	SCREAMING_SNAKE_CASE_ :			float			,	SCREAMING_SNAKE_CASE_ :			float			,	SCREAMING_SNAKE_CASE_ :			float			,	SCREAMING_SNAKE_CASE_ :			float )							->     tuple[float, float]:

       """simple docstring"""


       if not all(isinstance(SCREAMING_SNAKE_CASE_			,	(float, int) ) for val in locals().values() ):
              UpperCAmelCase  =						f"Input values must either be float or int: {list(locals().values() )}"
              raise TypeError(SCREAMING_SNAKE_CASE_ )
       UpperCAmelCase  =						((x * distance) / (z + distance)) * scale
       UpperCAmelCase  =						((y * distance) / (z + distance)) * scale
       return projected_x, projected_y
def       __snake_case		( SCREAMING_SNAKE_CASE_ :			float			,	SCREAMING_SNAKE_CASE_ :			float			,	SCREAMING_SNAKE_CASE_ :			float			,	SCREAMING_SNAKE_CASE_ :			str			,	SCREAMING_SNAKE_CASE_ :			float )							->     tuple[float, float, float]:

       """simple docstring"""


       if not isinstance(SCREAMING_SNAKE_CASE_			,	SCREAMING_SNAKE_CASE_ ):
              raise TypeError('''Axis must be a str''' )
       UpperCAmelCase  =						locals()
       del input_variables["axis"]
       if not all(isinstance(SCREAMING_SNAKE_CASE_			,	(float, int) ) for val in input_variables.values() ):
              UpperCAmelCase  =						(
                  '''Input values except axis must either be float or int: '''
                  f"{list(input_variables.values() )}"
              )
              raise TypeError(SCREAMING_SNAKE_CASE_ )
       UpperCAmelCase  =						(angle % 360) / 450 * 180 / math.pi
       if axis == "z":
              UpperCAmelCase  =						x * math.cos(SCREAMING_SNAKE_CASE_ ) - y * math.sin(SCREAMING_SNAKE_CASE_ )
              UpperCAmelCase  =						y * math.cos(SCREAMING_SNAKE_CASE_ ) + x * math.sin(SCREAMING_SNAKE_CASE_ )
              UpperCAmelCase  =						z
       elif axis == "x":
              UpperCAmelCase  =						y * math.cos(SCREAMING_SNAKE_CASE_ ) - z * math.sin(SCREAMING_SNAKE_CASE_ )
              UpperCAmelCase  =						z * math.cos(SCREAMING_SNAKE_CASE_ ) + y * math.sin(SCREAMING_SNAKE_CASE_ )
              UpperCAmelCase  =						x
       elif axis == "y":
              UpperCAmelCase  =						x * math.cos(SCREAMING_SNAKE_CASE_ ) - z * math.sin(SCREAMING_SNAKE_CASE_ )
              UpperCAmelCase  =						z * math.cos(SCREAMING_SNAKE_CASE_ ) + x * math.sin(SCREAMING_SNAKE_CASE_ )
              UpperCAmelCase  =						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) = }""")





from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType






class 						__magic_name__					(							snake_case				):
     UpperCamelCase_	:Dict										=      ["""image_processor""", """tokenizer"""]
     UpperCamelCase_	:str										=      """BridgeTowerImageProcessor"""
     UpperCamelCase_	:Tuple										=      ("""RobertaTokenizer""", """RobertaTokenizerFast""")






     def __init__(				self		,						_lowercase		,						_lowercase	)->     Any:
         super().__init__(_lowercase		,						_lowercase	)






     def __call__(				self		,						_lowercase		,						_lowercase = None		,						_lowercase = True		,						_lowercase = False		,						_lowercase = None		,						_lowercase = None		,						_lowercase = 0		,						_lowercase = None		,						_lowercase = None		,						_lowercase = None		,						_lowercase = False		,						_lowercase = False		,						_lowercase = False		,						_lowercase = False		,						_lowercase = True		,						_lowercase = None		,						**_lowercase		,						)->     BatchEncoding:
         UpperCamelCase_			  =						self.tokenizer(
             text=_lowercase		,						add_special_tokens=_lowercase		,						padding=_lowercase		,						truncation=_lowercase		,						max_length=_lowercase		,						stride=_lowercase		,						pad_to_multiple_of=_lowercase		,						return_token_type_ids=_lowercase		,						return_attention_mask=_lowercase		,						return_overflowing_tokens=_lowercase		,						return_special_tokens_mask=_lowercase		,						return_offsets_mapping=_lowercase		,						return_length=_lowercase		,						verbose=_lowercase		,						return_tensors=_lowercase		,						**_lowercase		,						)
         # add pixel_values + pixel_mask
         UpperCamelCase_			  =						self.image_processor(
             _lowercase		,						return_tensors=_lowercase		,						do_normalize=_lowercase		,						do_center_crop=_lowercase		,						**_lowercase	)
         encoding.update(_lowercase	)

         return encoding






     def 	UpperCAmelCase_				(				self		,						*_lowercase		,						**_lowercase	)->     Union[str, Any]:
         return self.tokenizer.batch_decode(*_lowercase		,						**_lowercase	)






     def 	UpperCAmelCase_				(				self		,						*_lowercase		,						**_lowercase	)->     List[Any]:
         return self.tokenizer.decode(*_lowercase		,						**_lowercase	)






     @property
     def 	UpperCAmelCase_				(				self	)->     Any:
         UpperCamelCase_			  =						self.tokenizer.model_input_names
         UpperCamelCase_			  =						self.image_processor.model_input_names
         return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names	)	)
