


from __future__ import annotations

import math

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


def 				lowerCamelCase__	(      a	:   float	,  a	:   float	,  a	:   float	,  a	:   float	,  a	:   float				)    ->	tuple[float, float]:





   """simple docstring"""
   if not all(isinstance(a	,  (float, int)				) for val in locals().values()				):
      a__ :str						  =    F'''Input values must either be float or int: {list(locals().values()				)}'''
      raise TypeError(a				)
   a__ :int						  =    ((x * distance) / (z + distance)) * scale
   a__ :List[str]						  =    ((y * distance) / (z + distance)) * scale
   return projected_x, projected_y


def 				lowerCamelCase__	(      a	:   float	,  a	:   float	,  a	:   float	,  a	:   str	,  a	:   float				)    ->	tuple[float, float, float]:





   """simple docstring"""
   if not isinstance(a	,  a				):
      raise TypeError("Axis must be a str"				)
   a__ :Optional[Any]						  =    locals()
   del input_variables["axis"]
   if not all(isinstance(a	,  (float, int)				) for val in input_variables.values()				):
      a__ :Optional[Any]						  =    (
          "Input values except axis must either be float or int: "
          F'''{list(input_variables.values()				)}'''
      )
      raise TypeError(a				)
   a__ :Union[str, Any]						  =    (angle % 360) / 450 * 180 / math.pi
   if axis == "z":
      a__ :Dict						  =    x * math.cos(a				) - y * math.sin(a				)
      a__ :Optional[Any]						  =    y * math.cos(a				) + x * math.sin(a				)
      a__ :Tuple						  =    z
   elif axis == "x":
      a__ :List[Any]						  =    y * math.cos(a				) - z * math.sin(a				)
      a__ :List[Any]						  =    z * math.cos(a				) + y * math.sin(a				)
      a__ :Any						  =    x
   elif axis == "y":
      a__ :Dict						  =    x * math.cos(a				) - z * math.sin(a				)
      a__ :List[str]						  =    z * math.cos(a				) + x * math.sin(a				)
      a__ :Any						  =    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 ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case__			 =						logging.get_logger(__name__)

snake_case__			 =						{
    '''google/pegasus-large''': '''https://huggingface.co/google/pegasus-large/resolve/main/config.json''',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}


class 					lowerCAmelCase_ (       _a):
						lowerCamelCase_         =     'pegasus'
						lowerCamelCase_         =     ['past_key_values']
						lowerCamelCase_         =     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}




						def __init__(	self						:   Any   ,     __A						:   Dict=50265   ,     __A						:   List[Any]=1024   ,     __A						:   int=12   ,     __A						:   Optional[Any]=4096   ,     __A						:   Optional[int]=16   ,     __A						:   Dict=12   ,     __A						:   List[Any]=4096   ,     __A						:   List[str]=16   ,     __A						:   Optional[int]=0.0   ,     __A						:   List[Any]=0.0   ,     __A						:   List[str]=True   ,     __A						:   Optional[int]=True   ,     __A						:   str="gelu"   ,     __A						:   Tuple=1024   ,     __A						:   Any=0.1   ,     __A						:   List[Any]=0.0   ,     __A						:   List[str]=0.0   ,     __A						:   Tuple=0.02   ,     __A						:   Union[str, Any]=0   ,     __A						:   Union[str, Any]=False   ,     __A						:   Optional[Any]=0   ,     __A						:   Tuple=1   ,     __A						:   str=1   ,     **__A						:   Any   ,     )      ->Union[str, Any]:






									"""simple docstring"""






									a__ :Any						  =    vocab_size
									a__ :List[str]						  =    max_position_embeddings
									a__ :int						  =    d_model
									a__ :Union[str, Any]						  =    encoder_ffn_dim
									a__ :List[Any]						  =    encoder_layers
									a__ :Union[str, Any]						  =    encoder_attention_heads
									a__ :Tuple						  =    decoder_ffn_dim
									a__ :List[Any]						  =    decoder_layers
									a__ :Tuple						  =    decoder_attention_heads
									a__ :Optional[int]						  =    dropout
									a__ :str						  =    attention_dropout
									a__ :Optional[int]						  =    activation_dropout
									a__ :str						  =    activation_function
									a__ :Dict						  =    init_std
									a__ :Any						  =    encoder_layerdrop
									a__ :int						  =    decoder_layerdrop
									a__ :Union[str, Any]						  =    use_cache
									a__ :List[Any]						  =    encoder_layers
									a__ :Dict						  =    scale_embedding  # scale factor will be sqrt(d_model) if True
									super().__init__(
									    pad_token_id=__A   ,     eos_token_id=__A   ,     is_encoder_decoder=__A   ,     decoder_start_token_id=__A   ,     forced_eos_token_id=__A   ,     **__A   ,     )




						@property
						def  _snake_case					(	self						:   Optional[Any]						)      ->int:






									"""simple docstring"""






									return self.encoder_attention_heads






						@property
						def  _snake_case					(	self						:   Union[str, Any]						)      ->int:






									"""simple docstring"""






									return self.d_model


