






'''simple docstring'''
from __future__ import annotations

import math

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




def 		__SCREAMING_SNAKE_CASE       (	_UpperCamelCase    ,		_UpperCamelCase    ,		_UpperCamelCase    ,		_UpperCamelCase    ,		_UpperCamelCase				):


   """simple docstring"""




   if not all(isinstance(_UpperCamelCase    ,		(float, int)				) for val in locals().values()				):
      lowercase_						:     int							     =  F"""Input values must either be float or int: {list(locals().values()				)}"""
      raise TypeError(_UpperCamelCase				)
   lowercase_						:     Optional[Any]							     =  ((x * distance) / (z + distance)) * scale
   lowercase_						:     Optional[int]							     =  ((y * distance) / (z + distance)) * scale
   return projected_x, projected_y




def 		__SCREAMING_SNAKE_CASE       (	_UpperCamelCase    ,		_UpperCamelCase    ,		_UpperCamelCase    ,		_UpperCamelCase    ,		_UpperCamelCase				):


   """simple docstring"""




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












'''simple docstring'''
import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


UpperCamelCase__			=      ['small', 'medium', 'large']

UpperCamelCase__			=      'lm_head.decoder.weight'
UpperCamelCase__			=      'lm_head.weight'




def 		__SCREAMING_SNAKE_CASE       (	_UpperCamelCase    ,		_UpperCamelCase				):


   """simple docstring"""




   lowercase_						:     Optional[Any]							     =  torch.load(_UpperCamelCase				)
   lowercase_						:     List[Any]							     =  d.pop(_UpperCamelCase				)
   os.makedirs(_UpperCamelCase    ,		exist_ok=_UpperCamelCase				)
   torch.save(_UpperCamelCase    ,		os.path.join(_UpperCamelCase    ,		_UpperCamelCase				)				)


if __name__ == "__main__":
 UpperCamelCase__			=      argparse.ArgumentParser()
 parser.add_argument('--dialogpt_path', default='.', type=str)
 UpperCamelCase__			=      parser.parse_args()
 for MODEL in DIALOGPT_MODELS:
  UpperCamelCase__			=      os.path.join(args.dialogpt_path, f"""{MODEL}_ft.pkl""")
  UpperCamelCase__			=      f"""./DialoGPT-{MODEL}"""
  convert_dialogpt_checkpoint(
      checkpoint_path,
      pytorch_dump_folder_path,
  )




