






'''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)

SCREAMING_SNAKE_CASE							=						[
    '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 UpperCAmelCase_       (     unittest.TestCase					):




      """simple docstring"""




      def 					A__   (			self      :		str  ,   UpperCAmelCase      :		str  ,   UpperCAmelCase      :		bool  ,   UpperCAmelCase      :		str = None  ,   UpperCAmelCase      :		list = None		)	->	Optional[int]:


       '''simple docstring'''

       lowercase       : Optional[Any]						=None
       lowercase       : Any						=os.path.abspath(os.path.join('''examples'''  ,   '''by_feature'''		)		)
       lowercase       : List[str]						=os.path.abspath('''examples'''		)
       for item in os.listdir(UpperCAmelCase		):
        if item not in EXCLUDE_EXAMPLES:
         lowercase       : Union[str, Any]						=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()'''  ,   ):
           lowercase       : List[Any]						=compare_against_test(
               os.path.join(UpperCAmelCase  ,   UpperCAmelCase		)  ,   UpperCAmelCase  ,   UpperCAmelCase  ,   UpperCAmelCase		)
           lowercase       : Optional[int]						='''\n'''.join(UpperCAmelCase		)
           if special_strings is not None:
            for string in special_strings:
             lowercase       : Optional[Any]						=diff.replace(UpperCAmelCase  ,   ''''''		)
           self.assertEqual(UpperCAmelCase  ,   ''''''		)






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


       '''simple docstring'''

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






      def 					A__   (			self      :		str		)	->	Any:


       '''simple docstring'''

       lowercase       : str						=os.path.abspath(os.path.join('''examples'''  ,   '''cv_example.py'''		)		)
       lowercase       : str						=[
           ''' ''' * 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 UpperCAmelCase_       (     __A					):




      """simple docstring"""




      UpperCamelCase_             =      False






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


       '''simple docstring'''

       super().setUpClass()
       lowercase       : List[str]						=tempfile.mkdtemp()
       lowercase       : Union[str, Any]						=os.path.join(cls._tmpdir  ,   '''default_config.yml'''		)

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






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


       '''simple docstring'''

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






      def 					A__   (			self      :		List[str]		)	->	Tuple:


       '''simple docstring'''

       lowercase       : Dict						=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      :		int		)	->	Union[str, Any]:


       '''simple docstring'''

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






      def 					A__   (			self      :		Union[str, Any]		)	->	Dict:


       '''simple docstring'''

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






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


       '''simple docstring'''

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


       '''simple docstring'''

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






      def 					A__   (			self      :		Any		)	->	Union[str, Any]:


       '''simple docstring'''

       lowercase       : Any						=['''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      :		int		)	->	List[str]:


       '''simple docstring'''

       with tempfile.TemporaryDirectory() as tmpdir:
        lowercase       : Tuple						=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      :		List[Any]		)	->	Optional[Any]:


       '''simple docstring'''

       lowercase       : Optional[Any]						=['''examples/by_feature/gradient_accumulation.py''']
       run_command(self._launch_args + testargs		)






      def 					A__   (			self      :		Dict		)	->	Tuple:


       '''simple docstring'''

       lowercase       : List[str]						=['''examples/by_feature/local_sgd.py''']
       run_command(self._launch_args + testargs		)











'''simple docstring'''



from queue import PriorityQueue
from typing import Any

import numpy as np


def 				lowercase_					(     __A			:							dict       ,   __A			:							str       ,   __A			:							set       ,   __A			:							set       ,   __A			:							dict       ,   __A			:							dict       ,   __A			:							PriorityQueue       ,   __A			:							dict       ,   __A			:							float | int       ,   )							->   float | int:



 """simple docstring"""




 for nxt, d in graph[v]:
  if nxt in visited_forward:
   continue
  lowercase       : str						=cst_fwd.get(__A       ,   np.inf      )
  lowercase       : str						=cst_fwd[v] + d
  if new_cost_f < old_cost_f:
   queue.put((new_cost_f, nxt)      )
   lowercase       : int						=new_cost_f
   lowercase       : Optional[int]						=v
  if nxt in visited_backward:
   if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
    lowercase       : List[Any]						=cst_fwd[v] + d + cst_bwd[nxt]
 return shortest_distance


def 				lowercase_					(     __A			:							str       ,   __A			:							str       ,   __A			:							dict       ,   __A			:							dict      )							->   int:



 """simple docstring"""




 lowercase       : Optional[Any]						=-1

 lowercase       : Tuple						=set()
 lowercase       : str						=set()
 lowercase       : List[str]						={source: 0}
 lowercase       : List[str]						={destination: 0}
 lowercase       : Tuple						={source: None}
 lowercase       : List[Any]						={destination: None}
 lowercase       : PriorityQueue[Any]						=PriorityQueue()
 lowercase       : PriorityQueue[Any]						=PriorityQueue()

 lowercase       : Any						=np.inf

 queue_forward.put((0, source)      )
 queue_backward.put((0, destination)      )

 if source == destination:
  return 0

 while not queue_forward.empty() and not queue_backward.empty():
  lowercase	,		lowercase       : int						=queue_forward.get()
  visited_forward.add(__A      )

  lowercase	,		lowercase       : int						=queue_backward.get()
  visited_backward.add(__A      )

  lowercase       : Dict						=pass_and_relaxation(
      __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   )

  lowercase       : List[Any]						=pass_and_relaxation(
      __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   __A       ,   )

  if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
   break

 if shortest_distance != np.inf:
  lowercase       : Union[str, Any]						=shortest_distance
 return shortest_path_distance


SCREAMING_SNAKE_CASE							=						{
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}
SCREAMING_SNAKE_CASE							=						{
    'B': [['E', 1]],
    'C': [['B', 1]],
    'D': [['C', 1]],
    'F': [['D', 1], ['G', 1]],
    'E': [[None, np.inf]],
    'G': [['E', 2]],
}

if __name__ == "__main__":
      import doctest

      doctest.testmod()



