




'''simple docstring'''



import sys
import turtle




def   lowercase__(			__UpperCamelCase:					tuple[float, float]      ,__UpperCamelCase:					tuple[float, float]    ):

      """simple docstring"""






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




def   lowercase__(			__UpperCamelCase:					tuple[float, float]      ,__UpperCamelCase:					tuple[float, float]      ,__UpperCamelCase:					tuple[float, float]      ,__UpperCamelCase:					int      ,):

      """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(__UpperCamelCase      ,get_mid(__UpperCamelCase      ,__UpperCamelCase    )      ,get_mid(__UpperCamelCase      ,__UpperCamelCase    )      ,depth - 1    )
      triangle(__UpperCamelCase      ,get_mid(__UpperCamelCase      ,__UpperCamelCase    )      ,get_mid(__UpperCamelCase      ,__UpperCamelCase    )      ,depth - 1    )
      triangle(__UpperCamelCase      ,get_mid(__UpperCamelCase      ,__UpperCamelCase    )      ,get_mid(__UpperCamelCase      ,__UpperCamelCase    )      ,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>"
            )
      UpperCamelCase_    	=				turtle.Turtle()
      my_pen.ht()
      my_pen.speed(5)
      my_pen.pencolor("red")

      UpperCamelCase_    	=				[(-1_7_5, -1_2_5), (0, 1_7_5), (1_7_5, -1_2_5)]  # vertices of triangle
      triangle(vertices[0], vertices[1], vertices[2], int(sys.argv[1]))









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase_							=				{
    """configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
    """tokenization_m2m_100""": ["""M2M100Tokenizer"""],
}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_							=				[
							    """M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """M2M100ForConditionalGeneration""",
							    """M2M100Model""",
							    """M2M100PreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
							from .tokenization_mam_aaa import MaMaaaTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mam_aaa import (
														    M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MaMaaaForConditionalGeneration,
														    MaMaaaModel,
														    MaMaaaPreTrainedModel,
														)


else:
							import sys

							UpperCAmelCase_							=				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)