


def UpperCamelCase_				(				__a      )	->   list:
      a__	:  Union[str, Any]     =   [0] * len(__a      )

      for i in range(1			,				len(__a      )      ):
            # use last results for better performance - dynamic programming
            a__	:  Dict     =   prefix_result[i - 1]
            while j > 0 and input_string[i] != input_string[j]:
                  a__	:  List[Any]     =   prefix_result[j - 1]

            if input_string[i] == input_string[j]:
                  j += 1
            a__	:  Any     =   j

      return prefix_result



def UpperCamelCase_				(				__a      )	->   int:
      return max(prefix_function(__a      )      )


if __name__ == "__main__":
    import doctest

    doctest.testmod()


"""simple docstring"""






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)

__lowerCAmelCase       :			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 					_A		(			unittest.TestCase      ):

      def 							A__			(		self						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase = None						,			__lowerCAmelCase = None		):







            """simple docstring"""



            lowercase								=      None
            lowercase								=      os.path.abspath(os.path.join("""examples"""						,			"""by_feature"""		)		)
            lowercase								=      os.path.abspath("""examples"""		)
            for item in os.listdir(__lowerCAmelCase		):
                  if item not in EXCLUDE_EXAMPLES:
                        lowercase								=      os.path.join(__lowerCAmelCase						,			__lowerCAmelCase		)
                        if os.path.isfile(__lowerCAmelCase		) and ".py" in item_path:
                              with self.subTest(
                                  tested_script=__lowerCAmelCase						,			feature_script=__lowerCAmelCase						,			tested_section="""main()""" if parser_only else """training_function()"""						,			):
                                    lowercase								=      compare_against_test(
                                        os.path.join(__lowerCAmelCase						,			__lowerCAmelCase		)						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		)
                                    lowercase								=      """\n""".join(__lowerCAmelCase		)
                                    if special_strings is not None:
                                          for string in special_strings:
                                                lowercase								=      diff.replace(__lowerCAmelCase						,			""""""		)
                                    self.assertEqual(__lowerCAmelCase						,			""""""		)

      def 							A__			(		self		):







            """simple docstring"""



            self.one_complete_example("""complete_nlp_example.py"""						,			__lowerCAmelCase		)
            self.one_complete_example("""complete_nlp_example.py"""						,			__lowerCAmelCase		)







      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      os.path.abspath(os.path.join("""examples"""						,			"""cv_example.py"""		)		)
            lowercase								=      [
                """ """ * 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"""						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		)
            self.one_complete_example("""complete_cv_example.py"""						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		)






@mock.patch.dict(os.environ    ,       {'TESTING_MOCKED_DATALOADERS': '1'}      )
class 					_A		(			lowerCAmelCase      ):
      snake_case__     :  Any				    =      False

      @classmethod
      def 							A__			(		cls		):







            """simple docstring"""



            super().setUpClass()
            lowercase								=      tempfile.mkdtemp()
            lowercase								=      os.path.join(cls._tmpdir						,			"""default_config.yml"""		)

            write_basic_config(save_location=cls.configPath		)
            lowercase								=      ["""accelerate""", """launch""", """--config_file""", cls.configPath]

      @classmethod
      def 							A__			(		cls		):







            """simple docstring"""



            super().tearDownClass()
            shutil.rmtree(cls._tmpdir		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      f'\n        examples/by_feature/checkpointing.py\n        --checkpointing_steps epoch\n        --output_dir {self.tmpdir}\n        '.split()
            run_command(self._launch_args + testargs		)
            self.assertTrue(os.path.exists(os.path.join(self.tmpdir						,			"""epoch_0"""		)		)		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      f'\n        examples/by_feature/checkpointing.py\n        --checkpointing_steps 1\n        --output_dir {self.tmpdir}\n        '.split()
            lowercase								=      run_command(self._launch_args + testargs		)
            self.assertTrue(os.path.exists(os.path.join(self.tmpdir						,			"""step_2"""		)		)		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      f'\n        examples/by_feature/checkpointing.py\n        --resume_from_checkpoint {os.path.join(self.tmpdir						,			"epoch_0"		)}\n        '.split()
            lowercase								=      run_command(self._launch_args + testargs						,			return_stdout=__lowerCAmelCase		)
            self.assertNotIn("""epoch 0:"""						,			__lowerCAmelCase		)
            self.assertIn("""epoch 1:"""						,			__lowerCAmelCase		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      f'\n        examples/by_feature/checkpointing.py\n        --resume_from_checkpoint {os.path.join(self.tmpdir						,			"step_2"		)}\n        '.split()
            lowercase								=      run_command(self._launch_args + testargs						,			return_stdout=__lowerCAmelCase		)
            if torch.cuda.is_available():
                  lowercase								=      torch.cuda.device_count()
            else:
                  lowercase								=      1
            if num_processes > 1:
                  self.assertNotIn("""epoch 0:"""						,			__lowerCAmelCase		)
                  self.assertIn("""epoch 1:"""						,			__lowerCAmelCase		)
            else:
                  self.assertIn("""epoch 0:"""						,			__lowerCAmelCase		)
                  self.assertIn("""epoch 1:"""						,			__lowerCAmelCase		)

      @slow
      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      """
        examples/by_feature/cross_validation.py
        --num_folds 2
        """.split()
            with mock.patch.dict(os.environ						,			{"""TESTING_MOCKED_DATALOADERS""": """0"""}		):
                  lowercase								=      run_command(self._launch_args + testargs						,			return_stdout=__lowerCAmelCase		)
                  lowercase								=      re.findall("""({.+})"""						,			__lowerCAmelCase		)
                  lowercase								=      [r for r in results if """accuracy""" in r][-1]
                  lowercase								=      ast.literal_eval(__lowerCAmelCase		)
                  self.assertGreaterEqual(results["""accuracy"""]						,			0.7_5		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      ["""examples/by_feature/multi_process_metrics.py"""]
            run_command(self._launch_args + testargs		)

      @require_trackers
      @mock.patch.dict(os.environ						,			{"""WANDB_MODE""": """offline"""}		)
      def 							A__			(		self		):







            """simple docstring"""



            with tempfile.TemporaryDirectory() as tmpdir:
                  lowercase								=      f'\n            examples/by_feature/tracking.py\n            --with_tracking\n            --project_dir {tmpdir}\n            '.split()
                  run_command(self._launch_args + testargs		)
                  self.assertTrue(os.path.exists(os.path.join(__lowerCAmelCase						,			"""tracking"""		)		)		)

      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      ["""examples/by_feature/gradient_accumulation.py"""]
            run_command(self._launch_args + testargs		)







      def 							A__			(		self		):







            """simple docstring"""



            lowercase								=      ["""examples/by_feature/local_sgd.py"""]
            run_command(self._launch_args + testargs		)



