






"""simple docstring"""





import json
import logging
import os
import sys
from time import time
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, require_torch_tpu


logging.basicConfig(level=logging.DEBUG)

lowerCamelCase      =		logging.getLogger()
def      a__			(   lowerCAmelCase__   ):
      UpperCAmelCase_    				=							{}
      UpperCAmelCase_    				=							os.path.join(lowerCAmelCase__			,    "all_results.json"   )
      if os.path.exists(lowerCAmelCase__   ):
            with open(lowerCAmelCase__			,    "r"   ) as f:
                  UpperCAmelCase_    				=							json.load(lowerCAmelCase__   )
      else:
            raise ValueError(f"""can't find {path}"""   )
      return results


lowerCamelCase      =		logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)


@require_torch_tpu
class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       def   lowercase__       (							self    :						Optional[Any]					)				->		Optional[int]:


             '''simple docstring'''




             import xla_spawn

             UpperCAmelCase_    				=							self.get_auto_remove_tmp_dir()
             UpperCAmelCase_    				=							F"""
            ./examples/pytorch/text-classification/run_glue.py
            --num_cores=8
            ./examples/pytorch/text-classification/run_glue.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --do_train
            --do_eval
            --debug tpu_metrics_debug
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --max_steps=10
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

             with patch.object(_UpperCAmelCase	,       "argv"	,       _UpperCAmelCase					):
                   UpperCAmelCase_    				=							time()
                   xla_spawn.main()
                   UpperCAmelCase_    				=							time()

                   UpperCAmelCase_    				=							get_results(_UpperCAmelCase					)
                   self.assertGreaterEqual(result["eval_accuracy"]	,       0.75					)

                   # Assert that the script takes less than 500 seconds to make sure it doesn't hang.
                   self.assertLess(end - start	,       500					)







       def   lowercase__       (							self    :						Union[str, Any]					)				->		List[str]:


             '''simple docstring'''




             import xla_spawn

             UpperCAmelCase_    				=							"\n            ./tests/test_trainer_tpu.py\n            --num_cores=8\n            ./tests/test_trainer_tpu.py\n            ".split()
             with patch.object(_UpperCAmelCase	,       "argv"	,       _UpperCAmelCase					):
                   xla_spawn.main()









"""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()




