

from __future__ import annotations

import math

UpperCamelCase__  :      Optional[int]			=    "2020.9.26"
UpperCamelCase__  :      str			=    "xcodz-dot, cclaus, dhruvmanila"


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		float ,   _SCREAMING_SNAKE_CASE					:		float ,   _SCREAMING_SNAKE_CASE					:		float ,   _SCREAMING_SNAKE_CASE					:		float ,   _SCREAMING_SNAKE_CASE					:		float       ):





    """simple docstring"""


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


def 					_UpperCAmelCase       (  _SCREAMING_SNAKE_CASE					:		float ,   _SCREAMING_SNAKE_CASE					:		float ,   _SCREAMING_SNAKE_CASE					:		float ,   _SCREAMING_SNAKE_CASE					:		str ,   _SCREAMING_SNAKE_CASE					:		float       ):





    """simple docstring"""


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


UpperCamelCase__  :      List[Any]			=    logging.get_logger(__name__)

UpperCamelCase__  :      List[str]			=    {
    "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json",
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}



class       __snake_case  (    lowerCAmelCase__       ):
  __lowerCAmelCase     :	Any						 =  'biogpt'

  def __init__(					self						,		_A=42384						,		_A=1024						,		_A=24						,		_A=16						,		_A=4096						,		_A="gelu"						,		_A=0.1						,		_A=0.1						,		_A=1024						,		_A=0.0_2						,		_A=1E-12						,		_A=True						,		_A=True						,		_A=0.0						,		_A=0.0						,		_A=1						,		_A=0						,		_A=2						,		**_A						,		):
      SCREAMING_SNAKE_CASE_									=						vocab_size
      SCREAMING_SNAKE_CASE_									=						max_position_embeddings
      SCREAMING_SNAKE_CASE_									=						hidden_size
      SCREAMING_SNAKE_CASE_									=						num_hidden_layers
      SCREAMING_SNAKE_CASE_									=						num_attention_heads
      SCREAMING_SNAKE_CASE_									=						intermediate_size
      SCREAMING_SNAKE_CASE_									=						hidden_act
      SCREAMING_SNAKE_CASE_									=						hidden_dropout_prob
      SCREAMING_SNAKE_CASE_									=						attention_probs_dropout_prob
      SCREAMING_SNAKE_CASE_									=						initializer_range
      SCREAMING_SNAKE_CASE_									=						layer_norm_eps
      SCREAMING_SNAKE_CASE_									=						scale_embedding
      SCREAMING_SNAKE_CASE_									=						use_cache
      SCREAMING_SNAKE_CASE_									=						layerdrop
      SCREAMING_SNAKE_CASE_									=						activation_dropout
      super().__init__(pad_token_id=_A						,		bos_token_id=_A						,		eos_token_id=_A						,		**_A)


