



"""simple docstring"""





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__)









"""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()




