




import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock

import torch

from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import write_basic_config


# DataLoaders built from `test_samples/MRPC` for quick testing
# Should mock `{script_name}.get_dataloaders` via:
# @mock.patch("{script_name}.get_dataloaders", mocked_dataloaders)

SCREAMING_SNAKE_CASE__       :      List[str]  =   [
    'cross_validation.py',
    'gradient_accumulation.py',
    'local_sgd.py',
    'multi_process_metrics.py',
    'memory.py',
    'automatic_gradient_accumulation.py',
    'fsdp_with_peak_mem_tracking.py',
    'deepspeed_with_config_support.py',
    'megatron_lm_gpt_pretraining.py',
]




class 		UpperCamelCase__	(unittest.TestCase     ):

    '''simple docstring'''



    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     ,  UpperCamelCase__ = None     )     ->      str:
           lowerCamelCase   :      Tuple			 =					None
           lowerCamelCase   :      str			 =					os.path.abspath(os.path.join("examples"     ,  "by_feature"     )     )
           lowerCamelCase   :      str			 =					os.path.abspath("examples"     )
           for item in os.listdir(UpperCamelCase__     ):
                  if item not in EXCLUDE_EXAMPLES:
                         lowerCamelCase   :      List[str]			 =					os.path.join(UpperCamelCase__     ,  UpperCamelCase__     )
                         if os.path.isfile(UpperCamelCase__     ) and ".py" in item_path:
                                with self.subTest(
                                    tested_script=UpperCamelCase__     ,  feature_script=UpperCamelCase__     ,  tested_section="main()" if parser_only else "training_function()"     ,  ):
                                       lowerCamelCase   :      Any			 =					compare_against_test(
                                           os.path.join(UpperCamelCase__     ,  UpperCamelCase__     )     ,  UpperCamelCase__     ,  UpperCamelCase__     ,  UpperCamelCase__     )
                                       lowerCamelCase   :      Dict			 =					"\n".join(UpperCamelCase__     )
                                       if special_strings is not None:
                                              for string in special_strings:
                                                     lowerCamelCase   :      Tuple			 =					diff.replace(UpperCamelCase__     ,  ""     )
                                       self.assertEqual(UpperCamelCase__     ,  ""     )







    def     _lowercase     (    self     )     ->      List[Any]:
           self.one_complete_example("complete_nlp_example.py"     ,  UpperCamelCase__     )
           self.one_complete_example("complete_nlp_example.py"     ,  UpperCamelCase__     )







    def     _lowercase     (    self     )     ->      Union[str, Any]:
           lowerCamelCase   :      Optional[Any]			 =					os.path.abspath(os.path.join("examples"     ,  "cv_example.py"     )     )
           lowerCamelCase   :      Tuple			 =					[
               " " * 16 + "{\n\n",
               " " * 20 + "\"accuracy\": eval_metric[\"accuracy\"],\n\n",
               " " * 20 + "\"f1\": eval_metric[\"f1\"],\n\n",
               " " * 20 + "\"train_loss\": total_loss.item() / len(train_dataloader),\n\n",
               " " * 20 + "\"epoch\": epoch,\n\n",
               " " * 16 + "},\n\n",
               " " * 16 + "step=epoch,\n",
               " " * 12,
               " " * 8 + "for step, batch in enumerate(active_dataloader):\n",
           ]
           self.one_complete_example("complete_cv_example.py"     ,  UpperCamelCase__     ,  UpperCamelCase__     ,  UpperCamelCase__     )
           self.one_complete_example("complete_cv_example.py"     ,  UpperCamelCase__     ,  UpperCamelCase__     ,  UpperCamelCase__     )




@mock.patch.dict(os.environ    ,				{"""TESTING_MOCKED_DATALOADERS""": """1"""}     )
class 		UpperCamelCase__	(lowerCAmelCase__     ):

    '''simple docstring'''



    lowerCamelCase_      :	Union[str, Any]	     =      False







    @classmethod
    def     _lowercase     (    cls     )     ->      str:
           super().setUpClass()
           lowerCamelCase   :      str			 =					tempfile.mkdtemp()
           lowerCamelCase   :      Tuple			 =					os.path.join(cls._tmpdir     ,  "default_config.yml"     )

           write_basic_config(save_location=cls.configPath     )
           lowerCamelCase   :      Optional[Any]			 =					["accelerate", "launch", "--config_file", cls.configPath]







    @classmethod
    def     _lowercase     (    cls     )     ->      List[Any]:
           super().tearDownClass()
           shutil.rmtree(cls._tmpdir     )







    def     _lowercase     (    self     )     ->      Union[str, Any]:
           lowerCamelCase   :      Union[str, Any]			 =					F'''
        examples/by_feature/checkpointing.py
        --checkpointing_steps epoch
        --output_dir {self.tmpdir}
        '''.split()
           run_command(self._launch_args + testargs     )
           self.assertTrue(os.path.exists(os.path.join(self.tmpdir     ,  "epoch_0"     )     )     )







    def     _lowercase     (    self     )     ->      List[Any]:
           lowerCamelCase   :      Optional[int]			 =					F'''
        examples/by_feature/checkpointing.py
        --checkpointing_steps 1
        --output_dir {self.tmpdir}
        '''.split()
           lowerCamelCase   :      Optional[Any]			 =					run_command(self._launch_args + testargs     )
           self.assertTrue(os.path.exists(os.path.join(self.tmpdir     ,  "step_2"     )     )     )







    def     _lowercase     (    self     )     ->      Any:
           lowerCamelCase   :      Optional[int]			 =					F'''
        examples/by_feature/checkpointing.py
        --resume_from_checkpoint {os.path.join(self.tmpdir     ,  "epoch_0"     )}
        '''.split()
           lowerCamelCase   :      List[Any]			 =					run_command(self._launch_args + testargs     ,  return_stdout=UpperCamelCase__     )
           self.assertNotIn("epoch 0:"     ,  UpperCamelCase__     )
           self.assertIn("epoch 1:"     ,  UpperCamelCase__     )







    def     _lowercase     (    self     )     ->      str:
           lowerCamelCase   :      int			 =					F'''
        examples/by_feature/checkpointing.py
        --resume_from_checkpoint {os.path.join(self.tmpdir     ,  "step_2"     )}
        '''.split()
           lowerCamelCase   :      Optional[int]			 =					run_command(self._launch_args + testargs     ,  return_stdout=UpperCamelCase__     )
           if torch.cuda.is_available():
                  lowerCamelCase   :      Optional[Any]			 =					torch.cuda.device_count()
           else:
                  lowerCamelCase   :      str			 =					1
           if num_processes > 1:
                  self.assertNotIn("epoch 0:"     ,  UpperCamelCase__     )
                  self.assertIn("epoch 1:"     ,  UpperCamelCase__     )
           else:
                  self.assertIn("epoch 0:"     ,  UpperCamelCase__     )
                  self.assertIn("epoch 1:"     ,  UpperCamelCase__     )







    @slow
    def     _lowercase     (    self     )     ->      Tuple:
           lowerCamelCase   :      Union[str, Any]			 =					"\n        examples/by_feature/cross_validation.py\n        --num_folds 2\n        ".split()
           with mock.patch.dict(os.environ     ,  {"TESTING_MOCKED_DATALOADERS": "0"}     ):
                  lowerCamelCase   :      Tuple			 =					run_command(self._launch_args + testargs     ,  return_stdout=UpperCamelCase__     )
                  lowerCamelCase   :      Optional[int]			 =					re.findall("({.+})"     ,  UpperCamelCase__     )
                  lowerCamelCase   :      Any			 =					[r for r in results if "accuracy" in r][-1]
                  lowerCamelCase   :      List[str]			 =					ast.literal_eval(UpperCamelCase__     )
                  self.assertGreaterEqual(results["accuracy"]     ,  0.75     )







    def     _lowercase     (    self     )     ->      str:
           lowerCamelCase   :      str			 =					["examples/by_feature/multi_process_metrics.py"]
           run_command(self._launch_args + testargs     )







    @require_trackers
    @mock.patch.dict(os.environ     ,  {"WANDB_MODE": "offline"}     )
    def     _lowercase     (    self     )     ->      Optional[int]:
           with tempfile.TemporaryDirectory() as tmpdir:
                  lowerCamelCase   :      Optional[int]			 =					F'''
            examples/by_feature/tracking.py
            --with_tracking
            --project_dir {tmpdir}
            '''.split()
                  run_command(self._launch_args + testargs     )
                  self.assertTrue(os.path.exists(os.path.join(UpperCamelCase__     ,  "tracking"     )     )     )







    def     _lowercase     (    self     )     ->      Optional[int]:
           lowerCamelCase   :      Union[str, Any]			 =					["examples/by_feature/gradient_accumulation.py"]
           run_command(self._launch_args + testargs     )







    def     _lowercase     (    self     )     ->      Any:
           lowerCamelCase   :      Tuple			 =					["examples/by_feature/local_sgd.py"]
           run_command(self._launch_args + testargs     )













import colorsys

from PIL import Image  # type: ignore







def  _SCREAMING_SNAKE_CASE				(   a					,						a					,						a  )      ->      float:
					__A	:						List[str]       =				x
					__A	:						str       =				y
					for step in range(a  ):  # noqa: B007
										__A	:						Union[str, Any]       =				a * a - b * b + x
										__A	:						Optional[int]       =				2 * a * b + y
										__A	:						List[str]       =				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  _SCREAMING_SNAKE_CASE				(   a  )      ->      tuple:
					if distance == 1:
										return (0, 0, 0)
					else:
										return (2_55, 2_55, 2_55)







def  _SCREAMING_SNAKE_CASE				(   a  )      ->      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  _SCREAMING_SNAKE_CASE				(   a = 8_00					,						a = 6_00					,						a = -0.6					,						a = 0					,						a = 3.2					,						a = 50					,						a = True					,						)      ->      Image.Image:
					__A	:						str       =				Image.new('RGB'					,						(image_width, image_height)  )
					__A	:						Dict       =				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
															__A	:						Dict       =				figure_width / image_width * image_height
															__A	:						Union[str, Any]       =				figure_center_x + (image_x / image_width - 0.5) * figure_width
															__A	:						Optional[Any]       =				figure_center_y + (image_y / image_height - 0.5) * figure_height

															__A	:						Union[str, Any]       =				get_distance(a					,						a					,						a  )

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

					return img


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				# colored version, full figure
				UpperCAmelCase						:   str			  =     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()




