
import sys
import turtle


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__		):
      return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		UpperCamelCase__ ,		):
      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>"
        )
    lowerCamelCase      =turtle.Turtle()
    my_pen.ht()
    my_pen.speed(5)
    my_pen.pencolor("red")

    lowerCamelCase      =[(-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_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCamelCase      ={
    "configuration_mobilebert": [
        "MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "MobileBertConfig",
        "MobileBertOnnxConfig",
    ],
    "tokenization_mobilebert": ["MobileBertTokenizer"],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =["MobileBertTokenizerFast"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "MobileBertForMaskedLM",
        "MobileBertForMultipleChoice",
        "MobileBertForNextSentencePrediction",
        "MobileBertForPreTraining",
        "MobileBertForQuestionAnswering",
        "MobileBertForSequenceClassification",
        "MobileBertForTokenClassification",
        "MobileBertLayer",
        "MobileBertModel",
        "MobileBertPreTrainedModel",
        "load_tf_weights_in_mobilebert",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFMobileBertForMaskedLM",
        "TFMobileBertForMultipleChoice",
        "TFMobileBertForNextSentencePrediction",
        "TFMobileBertForPreTraining",
        "TFMobileBertForQuestionAnswering",
        "TFMobileBertForSequenceClassification",
        "TFMobileBertForTokenClassification",
        "TFMobileBertMainLayer",
        "TFMobileBertModel",
        "TFMobileBertPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_mobilebert import (
        MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        MobileBertConfig,
        MobileBertOnnxConfig,
    )
    from .tokenization_mobilebert import MobileBertTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_mobilebert_fast import MobileBertTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mobilebert import (
            MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            MobileBertForMaskedLM,
            MobileBertForMultipleChoice,
            MobileBertForNextSentencePrediction,
            MobileBertForPreTraining,
            MobileBertForQuestionAnswering,
            MobileBertForSequenceClassification,
            MobileBertForTokenClassification,
            MobileBertLayer,
            MobileBertModel,
            MobileBertPreTrainedModel,
            load_tf_weights_in_mobilebert,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mobilebert import (
            TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFMobileBertForMaskedLM,
            TFMobileBertForMultipleChoice,
            TFMobileBertForNextSentencePrediction,
            TFMobileBertForPreTraining,
            TFMobileBertForQuestionAnswering,
            TFMobileBertForSequenceClassification,
            TFMobileBertForTokenClassification,
            TFMobileBertMainLayer,
            TFMobileBertModel,
            TFMobileBertPreTrainedModel,
        )

else:
    import sys

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


