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 				a							(			unittest.TestCase       ):







 """simple docstring"""






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



 def      UpperCAmelCase							(					self							)  ->					int:
        self.one_complete_example("""complete_nlp_example.py"""		,				lowerCAmelCase_							)
        self.one_complete_example("""complete_nlp_example.py"""		,				lowerCAmelCase_							)



 def      UpperCAmelCase							(					self							)  ->					Optional[int]:
        _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"""		,				lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_							)
        self.one_complete_example("""complete_cv_example.py"""		,				lowerCAmelCase_		,				lowerCAmelCase_		,				lowerCAmelCase_							)



@mock.patch.dict(os.environ       ,			{'''TESTING_MOCKED_DATALOADERS''': '''1'''}       )
class 				a							(			__lowerCAmelCase       ):







 """simple docstring"""






 lowerCamelCase	:Dict    			=		False



 @classmethod
 def      UpperCAmelCase							(					cls							)  ->					str:
        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      UpperCAmelCase							(					cls							)  ->					int:
        super().tearDownClass()
        shutil.rmtree(cls._tmpdir							)



 def      UpperCAmelCase							(					self							)  ->					Any:
        _A        =  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      UpperCAmelCase							(					self							)  ->					Union[str, Any]:
        _A        =  F'''
        examples/by_feature/checkpointing.py
        --checkpointing_steps 1
        --output_dir {self.tmpdir}
        '''.split()
        _A        =  run_command(self._launch_args + testargs							)
        self.assertTrue(os.path.exists(os.path.join(self.tmpdir		,				"""step_2"""							)							)							)



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



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



 @slow
 def      UpperCAmelCase							(					self							)  ->					Tuple:
        _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=lowerCAmelCase_							)
               _A        =  re.findall("""({.+})"""		,				lowerCAmelCase_							)
               _A        =  [r for r in results if """accuracy""" in r][-1]
               _A        =  ast.literal_eval(lowerCAmelCase_							)
               self.assertGreaterEqual(results["""accuracy"""]		,				0.75							)



 def      UpperCAmelCase							(					self							)  ->					Union[str, Any]:
        _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      UpperCAmelCase							(					self							)  ->					Optional[int]:
        with tempfile.TemporaryDirectory() as tmpdir:
               _A        =  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(lowerCAmelCase_		,				"""tracking"""							)							)							)



 def      UpperCAmelCase							(					self							)  ->					Any:
        _A        =  ["""examples/by_feature/gradient_accumulation.py"""]
        run_command(self._launch_args + testargs							)



 def      UpperCAmelCase							(					self							)  ->					Any:
        _A        =  ["""examples/by_feature/local_sgd.py"""]
        run_command(self._launch_args + testargs							)





from __future__ import annotations

_SCREAMING_SNAKE_CASE										=						{
    'A': ['B', 'C', 'E'],
    'B': ['A', 'D', 'E'],
    'C': ['A', 'F', 'G'],
    'D': ['B'],
    'E': ['A', 'B', 'D'],
    'F': ['C'],
    'G': ['C'],
}



class 				a							:







 """simple docstring"""






 def __init__(					self		,				lowerCAmelCase_		,				lowerCAmelCase_							)  ->					None:
        _A        =  graph
        # mapping node to its parent in resulting breadth first tree
        _A        =  {}
        _A        =  source_vertex



 def      UpperCAmelCase							(					self							)  ->					None:
        _A        =  {self.source_vertex}
        _A        =  None
        _A        =  [self.source_vertex]  # first in first out queue

        while queue:
               _A        =  queue.pop(0							)
               for adjacent_vertex in self.graph[vertex]:
                      if adjacent_vertex not in visited:
                             visited.add(lowerCAmelCase_							)
                             _A        =  vertex
                             queue.append(lowerCAmelCase_							)



 def      UpperCAmelCase							(					self		,				lowerCAmelCase_							)  ->					str:
        if target_vertex == self.source_vertex:
               return self.source_vertex

        _A        =  self.parent.get(lowerCAmelCase_							)
        if target_vertex_parent is None:
               _A        =  (
                   F'''No path from vertex: {self.source_vertex} to vertex: {target_vertex}'''
               )
               raise ValueError(lowerCAmelCase_							)

        return self.shortest_path(lowerCAmelCase_							) + F'''->{target_vertex}'''


if __name__ == "__main__":
    _SCREAMING_SNAKE_CASE										=						Graph(graph, 'G')
    g.breath_first_search()
    print(g.shortest_path('D'))
    print(g.shortest_path('G'))
    print(g.shortest_path('Foo'))




