
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)

lowercase__							:							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        SCREAMING_SNAKE_CASE__    (							unittest.TestCase    ):

							"""simple docstring"""






							def     A__		(  self     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_ = None     ,	SCREAMING_SNAKE_CASE_ = None			)->   int:





								'''simple docstring'''






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



							def     A__		(  self			)->   Any:





								'''simple docstring'''






								self.one_complete_example('''complete_nlp_example.py'''     ,	__UpperCamelCase			)
								self.one_complete_example('''complete_nlp_example.py'''     ,	__UpperCamelCase			)



							def     A__		(  self			)->   int:





								'''simple docstring'''






								__UpperCamelCase       =			os.path.abspath(os.path.join('''examples'''     ,	'''cv_example.py'''			)			)
								__UpperCamelCase       =			[
								    ''' ''' * 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        SCREAMING_SNAKE_CASE__    (							SCREAMING_SNAKE_CASE_    ):

							"""simple docstring"""






							_snake_case     		=  False



							@classmethod
							def     A__		(  cls			)->   Optional[Any]:





								'''simple docstring'''






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

								write_basic_config(save_location=cls.configPath			)
								__UpperCamelCase       =			['''accelerate''', '''launch''', '''--config_file''', cls.configPath]



							@classmethod
							def     A__		(  cls			)->   Any:





								'''simple docstring'''






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



							def     A__		(  self			)->   Any:





								'''simple docstring'''






								__UpperCamelCase       =			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			)->   Optional[int]:





								'''simple docstring'''






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



							def     A__		(  self			)->   List[Any]:





								'''simple docstring'''






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



							def     A__		(  self			)->   str:





								'''simple docstring'''






								__UpperCamelCase       =			F"\n        examples/by_feature/checkpointing.py\n        --resume_from_checkpoint {os.path.join(self.tmpdir     ,	'step_2'			)}\n        ".split()
								__UpperCamelCase       =			run_command(self._launch_args + testargs     ,	return_stdout=__UpperCamelCase			)
								if torch.cuda.is_available():
									__UpperCamelCase       =			torch.cuda.device_count()
								else:
									__UpperCamelCase       =			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     A__		(  self			)->   List[Any]:





								'''simple docstring'''






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



							def     A__		(  self			)->   List[Any]:





								'''simple docstring'''






								__UpperCamelCase       =			['''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			)->   Union[str, Any]:





								'''simple docstring'''






								with tempfile.TemporaryDirectory() as tmpdir:
									__UpperCamelCase       =			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(__UpperCamelCase     ,	'''tracking'''			)			)			)



							def     A__		(  self			)->   Dict:





								'''simple docstring'''






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



							def     A__		(  self			)->   Tuple:





								'''simple docstring'''






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






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__							:							int									=			{
    "configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"],
    "processing_git": ["GitProcessor"],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__							:							Tuple									=			[
				    "GIT_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "GitForCausalLM",
				    "GitModel",
				    "GitPreTrainedModel",
				    "GitVisionModel",
				]

if TYPE_CHECKING:
				from .configuration_git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitVisionConfig
				from .processing_git import GitProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_git import (
								    GIT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    GitForCausalLM,
								    GitModel,
								    GitPreTrainedModel,
								    GitVisionModel,
								)

else:
				import sys

				lowercase__							:							Optional[Any]									=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




