






from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase__       		=  logging.get_logger(__name__)

lowerCamelCase__       		=  {
    """EleutherAI/gpt-neox-20b""": """https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json""",
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}




class       snake_case__ (				lowercase_):

       '''simple docstring'''
       lowerCamelCase				:					List[Any]								=			"gpt_neox"



       def __init__(				self      ,    a__=5_04_32      ,    a__=61_44      ,    a__=44      ,    a__=64      ,    a__=2_45_76      ,    a__="gelu"      ,    a__=0.25      ,    a__=1_00_00      ,    a__=0.0      ,    a__=0.0      ,    a__=0.1      ,    a__=20_48      ,    a__=0.02      ,    a__=1e-5      ,    a__=True      ,    a__=0      ,    a__=2      ,    a__=False      ,    a__=True      ,    a__=None      ,    **a__      ,    )			->   Dict:






            '''simple docstring'''





            super().__init__(bos_token_id=a__      ,    eos_token_id=a__      ,    **a__     )
            __snake_case      :int 							=    vocab_size
            __snake_case      :Dict 							=    max_position_embeddings
            __snake_case      :List[Any] 							=    hidden_size
            __snake_case      :Any 							=    num_hidden_layers
            __snake_case      :Union[str, Any] 							=    num_attention_heads
            __snake_case      :Any 							=    intermediate_size
            __snake_case      :Union[str, Any] 							=    hidden_act
            __snake_case      :int 							=    rotary_pct
            __snake_case      :int 							=    rotary_emb_base
            __snake_case      :Optional[int] 							=    attention_dropout
            __snake_case      :List[str] 							=    hidden_dropout
            __snake_case      :Dict 							=    classifier_dropout
            __snake_case      :List[str] 							=    initializer_range
            __snake_case      :List[str] 							=    layer_norm_eps
            __snake_case      :str 							=    use_cache
            __snake_case      :Tuple 							=    tie_word_embeddings
            __snake_case      :Any 							=    use_parallel_residual
            __snake_case      :Tuple 							=    rope_scaling
            self._rope_scaling_validation()

            if self.hidden_size % self.num_attention_heads != 0:
                 raise ValueError(
                     """The hidden size is not divisble by the number of attention heads! Make sure to update them!"""     )



       def        __lowercase    (				self     )			->   Union[str, Any]:






            '''simple docstring'''





            if self.rope_scaling is None:
                 return

            if not isinstance(self.rope_scaling      ,    a__     ) or len(self.rope_scaling     ) != 2:
                 raise ValueError(
                     """`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, """
                     F'''got {self.rope_scaling}'''     )
            __snake_case      :Tuple 							=    self.rope_scaling.get("""type"""      ,    a__     )
            __snake_case      :int 							=    self.rope_scaling.get("""factor"""      ,    a__     )
            if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
                 raise ValueError(
                     F'''`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'''     )
            if rope_scaling_factor is None or not isinstance(a__      ,    a__     ) or rope_scaling_factor <= 1.0:
                 raise ValueError(F'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''     )










import colorsys

from PIL import Image  # type: ignore






def 	UpperCamelCase	(							snake_case__  : float						,snake_case__  : float						,snake_case__  : int	):




     '''simple docstring'''






     __snake_case      :List[Any] 							=    x
     __snake_case      :str 							=    y
     for step in range(snake_case__	):  # noqa: B007
          __snake_case      :Tuple 							=    a * a - b * b + x
          __snake_case      :Dict 							=    2 * a * b + y
          __snake_case      :str 							=    a_new

          # divergence happens for all complex number with an absolute value
          # greater than 4
          if a * a + b * b > 4:
               break
     return step / (max_step - 1)






def 	UpperCamelCase	(							snake_case__  : float	):




     '''simple docstring'''






     if distance == 1:
          return (0, 0, 0)
     else:
          return (255, 255, 255)






def 	UpperCamelCase	(							snake_case__  : float	):




     '''simple docstring'''






     if distance == 1:
          return (0, 0, 0)
     else:
          return tuple(round(i * 255	) for i in colorsys.hsv_to_rgb(snake_case__						,1						,1	)	)






def 	UpperCamelCase	(							snake_case__  : int = 800						,snake_case__  : int = 600						,snake_case__  : float = -0.6						,snake_case__  : float = 0						,snake_case__  : float = 3.2						,snake_case__  : int = 50						,snake_case__  : bool = True						,):




     '''simple docstring'''






     __snake_case      :Tuple 							=    Image.new("""RGB"""						,(image_width, image_height)	)
     __snake_case      :Dict 							=    img.load()

     # loop through the image-coordinates
     for image_x in range(snake_case__	):
          for image_y in range(snake_case__	):
               # determine the figure-coordinates based on the image-coordinates
               __snake_case      :Dict 							=    figure_width / image_width * image_height
               __snake_case      :Any 							=    figure_center_x + (image_x / image_width - 0.5) * figure_width
               __snake_case      :List[str] 							=    figure_center_y + (image_y / image_height - 0.5) * figure_height

               __snake_case      :Tuple 							=    get_distance(snake_case__						,snake_case__						,snake_case__	)

               # color the corresponding pixel based on the selected coloring-function
               if use_distance_color_coding:
                    __snake_case      :Optional[int] 							=    get_color_coded_rgb(snake_case__	)
               else:
                    __snake_case      :Optional[int] 							=    get_black_and_white_rgb(snake_case__	)

     return img


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     # colored version, full figure
     lowerCamelCase__       		=  get_image()

     # uncomment for colored version, different section, zoomed in
     # img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
     # figure_width = 0.8)

     # uncomment for black and white version, full figure
     # img = get_image(use_distance_color_coding = False)

     # uncomment to save the image
     # img.save("mandelbrot.png")

     img.show()


