




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__				:      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  ,		A  ,		A  ,		A = None  ,		A = None			)  ->   List[Any]:



          '''simple docstring'''



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







     def       lowerCAmelCase_    (     self			)  ->   Optional[int]:



          '''simple docstring'''



          self.one_complete_example("complete_nlp_example.py"  ,		A			)
          self.one_complete_example("complete_nlp_example.py"  ,		A			)







     def       lowerCAmelCase_    (     self			)  ->   Optional[int]:



          '''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"  ,		A  ,		A  ,		A			)
          self.one_complete_example("complete_cv_example.py"  ,		A  ,		A  ,		A			)







@mock.patch.dict(os.environ       , {"""TESTING_MOCKED_DATALOADERS""": """1"""}				)
class       a__	( UpperCamelCase__				):
     a		:      Any		 =     False







     @classmethod
     def       lowerCAmelCase_    (     cls			)  ->   Optional[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			)  ->   int:



          '''simple docstring'''



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







     def       lowerCAmelCase_    (     self			)  ->   Tuple:



          '''simple docstring'''



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



          '''simple docstring'''



          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       lowerCAmelCase_    (     self			)  ->   List[str]:



          '''simple docstring'''



          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=A			)
          self.assertNotIn("epoch 0:"  ,		A			)
          self.assertIn("epoch 1:"  ,		A			)







     def       lowerCAmelCase_    (     self			)  ->   Any:



          '''simple docstring'''



          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=A			)
          if torch.cuda.is_available():
               a     =				torch.cuda.device_count()
          else:
               a     =				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			)  ->   Optional[int]:



          '''simple docstring'''



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







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



          '''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			)  ->   str:



          '''simple docstring'''



          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(A  ,		"tracking"			)			)			)







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



          '''simple docstring'''



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







     def       lowerCAmelCase_    (     self			)  ->   Tuple:



          '''simple docstring'''



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







# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

lowercase__				:      str	   = TypeVar("T")




class       a__	( Generic[T]				):







     def __init__(     self  ,		A = True			)  ->   None:



          '''simple docstring'''



          a     =				{}  # dictionary of lists
          a     =				directed







     def       lowerCAmelCase_    (     self  ,		A  ,		A			)  ->   GraphAdjacencyList[T]:



          '''simple docstring'''



          if not self.directed:  # For undirected graphs
               # if both source vertex and destination vertex are both present in the
               # adjacency list, add destination vertex to source vertex list of adjacent
               # vertices and add source vertex to destination vertex list of adjacent
               # vertices.
               if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                    self.adj_list[source_vertex].append(A			)
                    self.adj_list[destination_vertex].append(A			)
               # if only source vertex is present in adjacency list, add destination vertex
               # to source vertex list of adjacent vertices, then create a new vertex with
               # destination vertex as key and assign a list containing the source vertex
               # as it's first adjacent vertex.
               elif source_vertex in self.adj_list:
                    self.adj_list[source_vertex].append(A			)
                    a     =				[source_vertex]
               # if only destination vertex is present in adjacency list, add source vertex
               # to destination vertex list of adjacent vertices, then create a new vertex
               # with source vertex as key and assign a list containing the source vertex
               # as it's first adjacent vertex.
               elif destination_vertex in self.adj_list:
                    self.adj_list[destination_vertex].append(A			)
                    a     =				[destination_vertex]
               # if both source vertex and destination vertex are not present in adjacency
               # list, create a new vertex with source vertex as key and assign a list
               # containing the destination vertex as it's first adjacent vertex also
               # create a new vertex with destination vertex as key and assign a list
               # containing the source vertex as it's first adjacent vertex.
               else:
                    a     =				[destination_vertex]
                    a     =				[source_vertex]
          else:  # For directed graphs
               # if both source vertex and destination vertex are present in adjacency
               # list, add destination vertex to source vertex list of adjacent vertices.
               if source_vertex in self.adj_list and destination_vertex in self.adj_list:
                    self.adj_list[source_vertex].append(A			)
               # if only source vertex is present in adjacency list, add destination
               # vertex to source vertex list of adjacent vertices and create a new vertex
               # with destination vertex as key, which has no adjacent vertex
               elif source_vertex in self.adj_list:
                    self.adj_list[source_vertex].append(A			)
                    a     =				[]
               # if only destination vertex is present in adjacency list, create a new
               # vertex with source vertex as key and assign a list containing destination
               # vertex as first adjacent vertex
               elif destination_vertex in self.adj_list:
                    a     =				[destination_vertex]
               # if both source vertex and destination vertex are not present in adjacency
               # list, create a new vertex with source vertex as key and a list containing
               # destination vertex as it's first adjacent vertex. Then create a new vertex
               # with destination vertex as key, which has no adjacent vertex
               else:
                    a     =				[destination_vertex]
                    a     =				[]

          return self







     def __repr__(     self			)  ->   str:



          '''simple docstring'''



          return pformat(self.adj_list			)

