



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)

__snake_case						:Optional[int]						=					[
    '''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 		_lowerCamelCase      (		self							:					List[Any]					,		__SCREAMING_SNAKE_CASE							:					str					,		__SCREAMING_SNAKE_CASE							:					bool					,		__SCREAMING_SNAKE_CASE							:					str = None					,		__SCREAMING_SNAKE_CASE							:					list = None):


           '''simple docstring'''

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



       def 		_lowerCamelCase      (		self							:					Tuple):


           '''simple docstring'''

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





       def 		_lowerCamelCase      (		self							:					Dict):


           '''simple docstring'''

           __a							=    os.path.abspath(os.path.join('''examples'''					,		'''cv_example.py'''))
           __a							=    [
               ''' ''' * 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'''					,		__SCREAMING_SNAKE_CASE					,		__SCREAMING_SNAKE_CASE					,		__SCREAMING_SNAKE_CASE)
           self.one_complete_example('''complete_cv_example.py'''					,		__SCREAMING_SNAKE_CASE					,		__SCREAMING_SNAKE_CASE					,		__SCREAMING_SNAKE_CASE)


@mock.patch.dict(os.environ				,{'''TESTING_MOCKED_DATALOADERS''': '''1'''}   )
class    _A	(     __UpperCAmelCase   ):
       UpperCamelCase__  :   List[str]						 =						False



       @classmethod
       def 		_lowerCamelCase      (		cls							:					int):


           '''simple docstring'''

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

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



       @classmethod
       def 		_lowerCamelCase      (		cls							:					Dict):


           '''simple docstring'''

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



       def 		_lowerCamelCase      (		self							:					Dict):


           '''simple docstring'''

           __a							=    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							:					str):


           '''simple docstring'''

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



       def 		_lowerCamelCase      (		self							:					Tuple):


           '''simple docstring'''

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



       def 		_lowerCamelCase      (		self							:					Tuple):


           '''simple docstring'''

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



       @slow
       def 		_lowerCamelCase      (		self							:					int):


           '''simple docstring'''

           __a							=    '''
        examples/by_feature/cross_validation.py
        --num_folds 2
        '''.split()
           with mock.patch.dict(os.environ					,		{'''TESTING_MOCKED_DATALOADERS''': '''0'''}):
               __a							=    run_command(self._launch_args + testargs					,		return_stdout=__SCREAMING_SNAKE_CASE)
               __a							=    re.findall('''({.+})'''					,		__SCREAMING_SNAKE_CASE)
               __a							=    [r for r in results if '''accuracy''' in r][-1]
               __a							=    ast.literal_eval(__SCREAMING_SNAKE_CASE)
               self.assertGreaterEqual(results['''accuracy''']					,		0.75)



       def 		_lowerCamelCase      (		self							:					Optional[int]):


           '''simple docstring'''

           __a							=    ['''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							:					int):


           '''simple docstring'''

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



       def 		_lowerCamelCase      (		self							:					List[Any]):


           '''simple docstring'''

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





       def 		_lowerCamelCase      (		self							:					Union[str, Any]):


           '''simple docstring'''

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










def 					__snake_case     (      _UpperCAmelCase       ,			_UpperCAmelCase    ):
    return base * power(_UpperCAmelCase       ,			(exponent - 1)    ) if exponent else 1


if __name__ == "__main__":
 print('''Raise base to the power of exponent using recursion...''')
 __snake_case						:List[Any]						=					int(input('''Enter the base: ''').strip())
 __snake_case						:Dict						=					int(input('''Enter the exponent: ''').strip())
 __snake_case						:int						=					power(base, abs(exponent))
 if exponent < 0:  # power() does not properly deal w/ negative exponents
  __snake_case						:Optional[Any]						=					1 / result
 print(f'{base} to the power of {exponent} is {result}')





