


"""simple docstring"""






def __lowercase     (      lowerCamelCase_  :      List[Any]  ):
				SCREAMING_SNAKE_CASE__     							=				[]
				SCREAMING_SNAKE_CASE__     							=				set({"(", "[", "{"}  )
				SCREAMING_SNAKE_CASE__     							=				set({")", "]", "}"}  )
				SCREAMING_SNAKE_CASE__     							=				{"{": "}", "[": "]", "(": ")"}

				for i in range(len(lowerCamelCase_  )  ):
								if s[i] in open_brackets:
												stack.append(s[i]  )

								elif s[i] in closed_brackets and (
								    len(lowerCamelCase_  ) == 0 or (len(lowerCamelCase_  ) > 0 and open_to_closed[stack.pop()] != s[i])
								):
												return False

				return len(lowerCamelCase_  ) == 0


def __lowercase     (      ):
				SCREAMING_SNAKE_CASE__     							=				input("Enter sequence of brackets: "  )
				if is_balanced(lowerCamelCase_  ):
								print(lowerCamelCase_						,					"is balanced"  )
				else:
								print(lowerCamelCase_						,					"is not balanced"  )


if __name__ == "__main__":
	main()




"""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     =  [
    '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 			lowerCamelCase_		(			unittest.TestCase   ):





				"""simple docstring"""







				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__       ,		UpperCAmelCase__       ,		UpperCAmelCase__ = None       ,		UpperCAmelCase__ = None     ):
								SCREAMING_SNAKE_CASE__     							=				None
								SCREAMING_SNAKE_CASE__     							=				os.path.abspath(os.path.join("examples"       ,		"by_feature"     )     )
								SCREAMING_SNAKE_CASE__     							=				os.path.abspath("examples"     )
								for item in os.listdir(UpperCAmelCase__     ):
												if item not in EXCLUDE_EXAMPLES:
																SCREAMING_SNAKE_CASE__     							=				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()"       ,		):
																								SCREAMING_SNAKE_CASE__     							=				compare_against_test(
																								    os.path.join(UpperCAmelCase__       ,		UpperCAmelCase__     )       ,		UpperCAmelCase__       ,		UpperCAmelCase__       ,		UpperCAmelCase__     )
																								SCREAMING_SNAKE_CASE__     							=				"\n".join(UpperCAmelCase__     )
																								if special_strings is not None:
																												for string in special_strings:
																																SCREAMING_SNAKE_CASE__     							=				diff.replace(UpperCAmelCase__       ,		""     )
																								self.assertEqual(UpperCAmelCase__       ,		""     )



				def   lowerCAmelCase__		(						self     ):
								self.one_complete_example("complete_nlp_example.py"       ,		UpperCAmelCase__     )
								self.one_complete_example("complete_nlp_example.py"       ,		UpperCAmelCase__     )






				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				os.path.abspath(os.path.join("examples"       ,		"cv_example.py"     )     )
								SCREAMING_SNAKE_CASE__     							=				[
								    " " * 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 			lowerCamelCase_		(			lowercase   ):





				"""simple docstring"""







				_lowerCAmelCase      :      Dict      							=					False



				@classmethod
				def   lowerCAmelCase__		(						cls     ):
								super().setUpClass()
								SCREAMING_SNAKE_CASE__     							=				tempfile.mkdtemp()
								SCREAMING_SNAKE_CASE__     							=				os.path.join(cls._tmpdir       ,		"default_config.yml"     )

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



				@classmethod
				def   lowerCAmelCase__		(						cls     ):
								super().tearDownClass()
								shutil.rmtree(cls._tmpdir     )



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



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



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				f'''
        examples/by_feature/checkpointing.py
        --resume_from_checkpoint {os.path.join(self.tmpdir       ,		"step_2"     )}
        '''.split()
								SCREAMING_SNAKE_CASE__     							=				run_command(self._launch_args + testargs       ,		return_stdout=UpperCAmelCase__     )
								if torch.cuda.is_available():
												SCREAMING_SNAKE_CASE__     							=				torch.cuda.device_count()
								else:
												SCREAMING_SNAKE_CASE__     							=				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   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				"\n        examples/by_feature/cross_validation.py\n        --num_folds 2\n        ".split()
								with mock.patch.dict(os.environ       ,		{"TESTING_MOCKED_DATALOADERS": "0"}     ):
												SCREAMING_SNAKE_CASE__     							=				run_command(self._launch_args + testargs       ,		return_stdout=UpperCAmelCase__     )
												SCREAMING_SNAKE_CASE__     							=				re.findall("({.+})"       ,		UpperCAmelCase__     )
												SCREAMING_SNAKE_CASE__     							=				[r for r in results if "accuracy" in r][-1]
												SCREAMING_SNAKE_CASE__     							=				ast.literal_eval(UpperCAmelCase__     )
												self.assertGreaterEqual(results["accuracy"]       ,		0.75     )



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				["examples/by_feature/multi_process_metrics.py"]
								run_command(self._launch_args + testargs     )



				@require_trackers
				@mock.patch.dict(os.environ       ,		{"WANDB_MODE": "offline"}     )
				def   lowerCAmelCase__		(						self     ):
								with tempfile.TemporaryDirectory() as tmpdir:
												SCREAMING_SNAKE_CASE__     							=				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   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				["examples/by_feature/gradient_accumulation.py"]
								run_command(self._launch_args + testargs     )






				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				["examples/by_feature/local_sgd.py"]
								run_command(self._launch_args + testargs     )
