



"""simple docstring"""





import colorsys

from PIL import Image  # type: ignore
def      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):
      UpperCAmelCase_    				=							x
      UpperCAmelCase_    				=							y
      for step in range(lowerCAmelCase__   ):  # noqa: B007
            UpperCAmelCase_    				=							a * a - b * b + x
            UpperCAmelCase_    				=							2 * a * b + y
            UpperCAmelCase_    				=							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      a__			(   lowerCAmelCase__   ):
      if distance == 1:
            return (0, 0, 0)
      else:
            return (255, 255, 255)
def      a__			(   lowerCAmelCase__   ):
      if distance == 1:
            return (0, 0, 0)
      else:
            return tuple(round(i * 255   ) for i in colorsys.hsv_to_rgb(lowerCAmelCase__			,    1			,    1   )   )
def      a__			(   lowerCAmelCase__ = 800			,    lowerCAmelCase__ = 600			,    lowerCAmelCase__ = -0.6			,    lowerCAmelCase__ = 0			,    lowerCAmelCase__ = 3.2			,    lowerCAmelCase__ = 50			,    lowerCAmelCase__ = True			,    ):
      UpperCAmelCase_    				=							Image.new("RGB"			,    (image_width, image_height)   )
      UpperCAmelCase_    				=							img.load()

      # loop through the image-coordinates
      for image_x in range(lowerCAmelCase__   ):
            for image_y in range(lowerCAmelCase__   ):
                  # determine the figure-coordinates based on the image-coordinates
                  UpperCAmelCase_    				=							figure_width / image_width * image_height
                  UpperCAmelCase_    				=							figure_center_x + (image_x / image_width - 0.5) * figure_width
                  UpperCAmelCase_    				=							figure_center_y + (image_y / image_height - 0.5) * figure_height

                  UpperCAmelCase_    				=							get_distance(lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   )

                  # color the corresponding pixel based on the selected coloring-function
                  if use_distance_color_coding:
                        UpperCAmelCase_    				=							get_color_coded_rgb(lowerCAmelCase__   )
                  else:
                        UpperCAmelCase_    				=							get_black_and_white_rgb(lowerCAmelCase__   )

      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()









"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase      =		logging.get_logger(__name__)

lowerCamelCase      =		{
    """YituTech/conv-bert-base""": """https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json""",
    """YituTech/conv-bert-medium-small""": (
        """https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"""
    ),
    """YituTech/conv-bert-small""": """https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json""",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}
class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       UpperCamelCase		=  '''convbert'''



       def __init__(							self    :						Any	,       _UpperCAmelCase    :						Optional[int]=30522	,       _UpperCAmelCase    :						Tuple=768	,       _UpperCAmelCase    :						Optional[int]=12	,       _UpperCAmelCase    :						Dict=12	,       _UpperCAmelCase    :						Any=3072	,       _UpperCAmelCase    :						Dict="gelu"	,       _UpperCAmelCase    :						Optional[int]=0.1	,       _UpperCAmelCase    :						str=0.1	,       _UpperCAmelCase    :						Tuple=512	,       _UpperCAmelCase    :						Optional[Any]=2	,       _UpperCAmelCase    :						Union[str, Any]=0.02	,       _UpperCAmelCase    :						Dict=1e-12	,       _UpperCAmelCase    :						Optional[int]=1	,       _UpperCAmelCase    :						int=0	,       _UpperCAmelCase    :						Optional[Any]=2	,       _UpperCAmelCase    :						List[Any]=768	,       _UpperCAmelCase    :						Optional[int]=2	,       _UpperCAmelCase    :						str=9	,       _UpperCAmelCase    :						List[Any]=1	,       _UpperCAmelCase    :						Optional[Any]=None	,       **_UpperCAmelCase    :						str	,       )				->		List[Any]:


             '''simple docstring'''




             super().__init__(
                 pad_token_id=_UpperCAmelCase	,       bos_token_id=_UpperCAmelCase	,       eos_token_id=_UpperCAmelCase	,       **_UpperCAmelCase	,       )

             UpperCAmelCase_    				=							vocab_size
             UpperCAmelCase_    				=							hidden_size
             UpperCAmelCase_    				=							num_hidden_layers
             UpperCAmelCase_    				=							num_attention_heads
             UpperCAmelCase_    				=							intermediate_size
             UpperCAmelCase_    				=							hidden_act
             UpperCAmelCase_    				=							hidden_dropout_prob
             UpperCAmelCase_    				=							attention_probs_dropout_prob
             UpperCAmelCase_    				=							max_position_embeddings
             UpperCAmelCase_    				=							type_vocab_size
             UpperCAmelCase_    				=							initializer_range
             UpperCAmelCase_    				=							layer_norm_eps
             UpperCAmelCase_    				=							embedding_size
             UpperCAmelCase_    				=							head_ratio
             UpperCAmelCase_    				=							conv_kernel_size
             UpperCAmelCase_    				=							num_groups
             UpperCAmelCase_    				=							classifier_dropout



class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       @property
       def   lowercase__       (							self    :						Dict					)				->		Mapping[str, Mapping[int, str]]:


             '''simple docstring'''




             if self.task == "multiple-choice":
                   UpperCAmelCase_    				=							{0: "batch", 1: "choice", 2: "sequence"}
             else:
                   UpperCAmelCase_    				=							{0: "batch", 1: "sequence"}
             return OrderedDict(
                 [
                     ("input_ids", dynamic_axis),
                     ("attention_mask", dynamic_axis),
                     ("token_type_ids", dynamic_axis),
                 ]					)




