





"""simple docstring"""
import os

from bleurt import score  # From: git+https://github.com/google-research/bleurt.git

import datasets


lowerCamelCase_       =		datasets.logging.get_logger(__name__)


lowerCamelCase_       =		"\\n@inproceedings{bleurt,\n  title={BLEURT: Learning Robust Metrics for Text Generation},\n  author={Thibault Sellam and Dipanjan Das and Ankur P. Parikh},\n  booktitle={ACL},\n  year={2020},\n  url={https://arxiv.org/abs/2004.04696}\n}\n"

lowerCamelCase_       =		"\\nBLEURT a learnt evaluation metric for Natural Language Generation. It is built using multiple phases of transfer learning starting from a pretrained BERT model (Devlin et al. 2018)\nand then employing another pre-training phrase using synthetic data. Finally it is trained on WMT human annotations. You may run BLEURT out-of-the-box or fine-tune\nit for your specific application (the latter is expected to perform better).\n\nSee the project's README at https://github.com/google-research/bleurt#readme for more information.\n"

lowerCamelCase_       =		"\nBLEURT score.\n\nArgs:\n    `predictions` (list of str): prediction/candidate sentences\n    `references` (list of str): reference sentences\n    `checkpoint` BLEURT checkpoint. Will default to BLEURT-tiny if None.\n\nReturns:\n    'scores': List of scores.\nExamples:\n\n    >>> predictions = [\"hello there\", \"general kenobi\"]\n    >>> references = [\"hello there\", \"general kenobi\"]\n    >>> bleurt = datasets.load_metric(\"bleurt\")\n    >>> results = bleurt.compute(predictions=predictions, references=references)\n    >>> print([round(v, 2) for v in results[\"scores\"]])\n    [1.03, 1.04]\n"

lowerCamelCase_       =		{
    "bleurt-tiny-128": "https://storage.googleapis.com/bleurt-oss/bleurt-tiny-128.zip",
    "bleurt-tiny-512": "https://storage.googleapis.com/bleurt-oss/bleurt-tiny-512.zip",
    "bleurt-base-128": "https://storage.googleapis.com/bleurt-oss/bleurt-base-128.zip",
    "bleurt-base-512": "https://storage.googleapis.com/bleurt-oss/bleurt-base-512.zip",
    "bleurt-large-128": "https://storage.googleapis.com/bleurt-oss/bleurt-large-128.zip",
    "bleurt-large-512": "https://storage.googleapis.com/bleurt-oss/bleurt-large-512.zip",
    "BLEURT-20-D3": "https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D3.zip",
    "BLEURT-20-D6": "https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D6.zip",
    "BLEURT-20-D12": "https://storage.googleapis.com/bleurt-oss-21/BLEURT-20-D12.zip",
    "BLEURT-20": "https://storage.googleapis.com/bleurt-oss-21/BLEURT-20.zip",
}






@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION   ,     _KWARGS_DESCRIPTION  )
class  _SCREAMING_SNAKE_CASE(       datasets.Metric  ):




       def    _UpperCamelCase					(						self							)      ->				str:





             """simple docstring"""






             return datasets.MetricInfo(
                 description=_DESCRIPTION		,citation=_CITATION		,homepage='''https://github.com/google-research/bleurt'''		,inputs_description=_KWARGS_DESCRIPTION		,features=datasets.Features(
                     {
                         '''predictions''': datasets.Value('''string'''		,id='''sequence'''							),
                         '''references''': datasets.Value('''string'''		,id='''sequence'''							),
                     }							)		,codebase_urls=['''https://github.com/google-research/bleurt''']		,reference_urls=['''https://github.com/google-research/bleurt''', '''https://arxiv.org/abs/2004.04696''']		,)




       def    _UpperCamelCase					(						self		,SCREAMING_SNAKE_CASE__							)      ->				Dict:





             """simple docstring"""






             if self.config_name == "default":
                   logger.warning(
                       '''Using default BLEURT-Base checkpoint for sequence maximum length 128. '''
                       '''You can use a bigger model for better results with e.g.: datasets.load_metric(\'bleurt\', \'bleurt-large-512\').'''							)
                   __SCREAMING_SNAKE_CASE       :Union[str, Any]		    =  '''bleurt-base-128'''

             if self.config_name.lower() in CHECKPOINT_URLS:
                   __SCREAMING_SNAKE_CASE       :Tuple		    =  self.config_name.lower()

             elif self.config_name.upper() in CHECKPOINT_URLS:
                   __SCREAMING_SNAKE_CASE       :Optional[int]		    =  self.config_name.upper()

             else:
                   raise KeyError(
                       f'''{self.config_name} model not found. You should supply the name of a model checkpoint for bleurt in {CHECKPOINT_URLS.keys()}'''							)

             # download the model checkpoint specified by self.config_name and set up the scorer
             __SCREAMING_SNAKE_CASE       :Optional[int]		    =  dl_manager.download_and_extract(CHECKPOINT_URLS[checkpoint_name]							)
             __SCREAMING_SNAKE_CASE       :Any		    =  score.BleurtScorer(os.path.join(SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__							)							)




       def    _UpperCamelCase					(						self		,SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__							)      ->				List[str]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE       :List[str]		    =  self.scorer.score(references=SCREAMING_SNAKE_CASE__		,candidates=SCREAMING_SNAKE_CASE__							)
             return {"scores": scores}






"""simple docstring"""
import colorsys

from PIL import Image  # type: ignore



def 					__lowerCamelCase       (							a_					:		float			,       a_					:		float			,       a_					:		int							)      ->				float:
      __SCREAMING_SNAKE_CASE       :List[Any]		    =  x
      __SCREAMING_SNAKE_CASE       :List[Any]		    =  y
      for step in range(a_							):  # noqa: B007
            __SCREAMING_SNAKE_CASE       :Dict		    =  a * a - b * b + x
            __SCREAMING_SNAKE_CASE       :Tuple		    =  2 * a * b + y
            __SCREAMING_SNAKE_CASE       :Dict		    =  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 					__lowerCamelCase       (							a_					:		float							)      ->				tuple:
      if distance == 1:
            return (0, 0, 0)
      else:
            return (2_55, 2_55, 2_55)



def 					__lowerCamelCase       (							a_					:		float							)      ->				tuple:
      if distance == 1:
            return (0, 0, 0)
      else:
            return tuple(round(i * 2_55							) for i in colorsys.hsv_to_rgb(a_			,       1			,       1							)							)



def 					__lowerCamelCase       (							a_					:		int = 8_00			,       a_					:		int = 6_00			,       a_					:		float = -0.6			,       a_					:		float = 0			,       a_					:		float = 3.2			,       a_					:		int = 50			,       a_					:		bool = True			,       )      ->				Image.Image:
      __SCREAMING_SNAKE_CASE       :Optional[int]		    =  Image.new('''RGB'''			,       (image_width, image_height)							)
      __SCREAMING_SNAKE_CASE       :Tuple		    =  img.load()

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

                  __SCREAMING_SNAKE_CASE       :List[Any]		    =  get_distance(a_			,       a_			,       a_							)

                  # color the corresponding pixel based on the selected coloring-function
                  if use_distance_color_coding:
                        __SCREAMING_SNAKE_CASE       :Optional[int]		    =  get_color_coded_rgb(a_							)
                  else:
                        __SCREAMING_SNAKE_CASE       :Optional[Any]		    =  get_black_and_white_rgb(a_							)

      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()