




import sys
import turtle




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_      )       ->	tuple[float, float]:

    """simple docstring"""


    return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2




def 					__SCREAMING_SNAKE_CASE   (  lowercase_					,     lowercase_					,     lowercase_					,     lowercase_					,     )       ->	None:

    """simple docstring"""


    my_pen.up()
    my_pen.goto(vertexa[0]					,     vertexa[1]      )
    my_pen.down()
    my_pen.goto(vertexa[0]					,     vertexa[1]      )
    my_pen.goto(vertexa[0]					,     vertexa[1]      )
    my_pen.goto(vertexa[0]					,     vertexa[1]      )

    if depth == 0:
        return

    triangle(lowercase_					,     get_mid(lowercase_					,     lowercase_      )					,     get_mid(lowercase_					,     lowercase_      )					,     depth - 1      )
    triangle(lowercase_					,     get_mid(lowercase_					,     lowercase_      )					,     get_mid(lowercase_					,     lowercase_      )					,     depth - 1      )
    triangle(lowercase_					,     get_mid(lowercase_					,     lowercase_      )					,     get_mid(lowercase_					,     lowercase_      )					,     depth - 1      )


if __name__ == "__main__":
 if len(sys.argv) != 2:
  raise ValueError(
      "Correct format for using this script: "
      "python fractals.py <int:depth_for_fractal>"
  )
 a_   		=     turtle.Turtle()
 my_pen.ht()
 my_pen.speed(5)
 my_pen.pencolor("red")

 a_   		=     [(-175, -125), (0, 175), (175, -125)]  # vertices of triangle
 triangle(vertices[0], vertices[1], vertices[2], int(sys.argv[1]))












from collections import OrderedDict
from typing import Mapping

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


a_   		=     logging.get_logger(__name__)

a_   		=     {
    "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json",
    "google/bigbird-roberta-large": "https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json",
    "google/bigbird-base-trivia-itc": "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json",
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}

class  _lowerCamelCase						(			_SCREAMING_SNAKE_CASE   ):

      """simple docstring"""

      lowerCAmelCase__			: str    =					"big_bird"







      def __init__(     self					: str ,       snake_case					: Optional[Any]=50358 ,       snake_case					: Union[str, Any]=768 ,       snake_case					: Dict=12 ,       snake_case					: List[Any]=12 ,       snake_case					: Tuple=3072 ,       snake_case					: Tuple="gelu_new" ,       snake_case					: Dict=0.1 ,       snake_case					: Any=0.1 ,       snake_case					: List[Any]=4096 ,       snake_case					: Union[str, Any]=2 ,       snake_case					: Union[str, Any]=0.02 ,       snake_case					: Union[str, Any]=1E-12 ,       snake_case					: List[Any]=True ,       snake_case					: List[Any]=0 ,       snake_case					: int=1 ,       snake_case					: int=2 ,       snake_case					: Any=66 ,       snake_case					: str="block_sparse" ,       snake_case					: Any=True ,       snake_case					: Tuple=False ,       snake_case					: List[Any]=64 ,       snake_case					: Dict=3 ,       snake_case					: Union[str, Any]=None ,       **snake_case					: Any ,       ):
          super().__init__(
              pad_token_id=snake_case ,       bos_token_id=snake_case ,       eos_token_id=snake_case ,       sep_token_id=snake_case ,       **snake_case ,       )

          __UpperCamelCase  		=						vocab_size
          __UpperCamelCase  		=						max_position_embeddings
          __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  		=						initializer_range
          __UpperCamelCase  		=						type_vocab_size
          __UpperCamelCase  		=						layer_norm_eps
          __UpperCamelCase  		=						use_cache

          __UpperCamelCase  		=						rescale_embeddings
          __UpperCamelCase  		=						attention_type
          __UpperCamelCase  		=						use_bias
          __UpperCamelCase  		=						block_size
          __UpperCamelCase  		=						num_random_blocks
          __UpperCamelCase  		=						classifier_dropout







class  _lowerCamelCase						(			_SCREAMING_SNAKE_CASE   ):

      """simple docstring"""

      @property
      def       snake_case	(     self					: int				):
          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),
              ]				)






