


'''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 					_lowerCamelCase	(						unittest.TestCase							):



		'''simple docstring'''







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







		def        __lowerCAmelCase		( self		:						Union[str, Any]      )  ->			Optional[Any]:
			self.one_complete_example('complete_nlp_example.py'  ,					_A      )
			self.one_complete_example('complete_nlp_example.py'  ,					_A      )







		def        __lowerCAmelCase		( self		:						str      )  ->			Any:
			__magic_name__	:   Dict					     =					os.path.abspath(os.path.join('examples'  ,					'cv_example.py'      )      )
			__magic_name__	:   Dict					     =					[
			    ' ' * 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'  ,					_A  ,					_A  ,					_A      )
			self.one_complete_example('complete_cv_example.py'  ,					_A  ,					_A  ,					_A      )







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



		'''simple docstring'''







		A_     :      str				   =    False







		@classmethod
		def        __lowerCAmelCase		( cls		:						str      )  ->			List[str]:
			super().setUpClass()
			__magic_name__	:   str					     =					tempfile.mkdtemp()
			__magic_name__	:   Tuple					     =					os.path.join(cls._tmpdir  ,					'default_config.yml'      )

			write_basic_config(save_location=cls.configPath      )
			__magic_name__	:   List[str]					     =					['accelerate', 'launch', '--config_file', cls.configPath]







		@classmethod
		def        __lowerCAmelCase		( cls		:						Tuple      )  ->			Tuple:
			super().tearDownClass()
			shutil.rmtree(cls._tmpdir      )







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			Union[str, Any]:
			__magic_name__	:   List[str]					     =					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        __lowerCAmelCase		( self		:						List[Any]      )  ->			str:
			__magic_name__	:   List[str]					     =					F'\n        examples/by_feature/checkpointing.py\n        --checkpointing_steps 1\n        --output_dir {self.tmpdir}\n        '.split()
			__magic_name__	:   int					     =					run_command(self._launch_args + testargs      )
			self.assertTrue(os.path.exists(os.path.join(self.tmpdir  ,					'step_2'      )      )      )







		def        __lowerCAmelCase		( self		:						List[str]      )  ->			Tuple:
			__magic_name__	:   List[Any]					     =					F'\n        examples/by_feature/checkpointing.py\n        --resume_from_checkpoint {os.path.join(self.tmpdir  ,					"epoch_0"      )}\n        '.split()
			__magic_name__	:   Optional[Any]					     =					run_command(self._launch_args + testargs  ,					return_stdout=_A      )
			self.assertNotIn('epoch 0:'  ,					_A      )
			self.assertIn('epoch 1:'  ,					_A      )







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







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







		def        __lowerCAmelCase		( self		:						Any      )  ->			str:
			__magic_name__	:   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        __lowerCAmelCase		( self		:						str      )  ->			Any:
			with tempfile.TemporaryDirectory() as tmpdir:
				__magic_name__	:   Union[str, Any]					     =					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(_A  ,					'tracking'      )      )      )







		def        __lowerCAmelCase		( self		:						int      )  ->			Dict:
			__magic_name__	:   Optional[Any]					     =					['examples/by_feature/gradient_accumulation.py']
			run_command(self._launch_args + testargs      )







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			Any:
			__magic_name__	:   Dict					     =					['examples/by_feature/local_sgd.py']
			run_command(self._launch_args + testargs      )



'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


lowerCAmelCase				:Tuple        =      logging.get_logger(__name__)
class _lowerCamelCase	(						lowercase__							):



		'''simple docstring'''







		def __init__( self		:						Any  ,					*_A		:						List[Any]  ,					**_A		:						str      )  ->			None:
			warnings.warn(
			    'The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
			    ' use BeitImageProcessor instead.'  ,					_A  ,					)
			super().__init__(*_A  ,					**_A      )