




import torch

from accelerate import Accelerator, DistributedType







class 				UpperCAmelCase:



	"""simple docstring"""






	def __enter__(					self    ) ->      Tuple:





								"""simple docstring"""


								if self.enabled:
															lowercase__  :	Dict        =							self.model.no_sync()
															self.model_sync_obj.__enter__()

								return self

	def __exit__(					self	,				lowerCamelCase	,				lowerCamelCase	,				lowerCamelCase    ) ->      Any:





								"""simple docstring"""


								if self.enabled:
															# Average all models on exit
															self._sync_and_avg_model_params()
															self.model_sync_obj.__exit__(lowerCamelCase	,				lowerCamelCase	,				lowerCamelCase    )

	def __init__(					self	,				lowerCamelCase	,				lowerCamelCase	,				lowerCamelCase	,				lowerCamelCase = True    ) ->      Optional[Any]:





								"""simple docstring"""


								if accelerator.distributed_type not in [
								    DistributedType.NO,
								    DistributedType.MULTI_CPU,
								    DistributedType.MULTI_GPU,
								]:
															raise NotImplementedError("LocalSGD is supported only for CPUs and GPUs (no DeepSpeed or MegatronLM)"    )
								lowercase__  :	Optional[int]        =							enabled and accelerator.distributed_type != DistributedType.NO
								lowercase__  :	Union[str, Any]        =							0
								if self.enabled:
															lowercase__  :	Tuple        =							accelerator
															lowercase__  :	Optional[Any]        =							model
															lowercase__  :	int        =							local_sgd_steps

	def    __a     (					self    ) ->      List[str]:





								"""simple docstring"""


								self.num_steps += 1
								if not self.enabled:
															return

								if self.num_steps % self.local_sgd_steps == 0:
															self._sync_and_avg_model_params()







	def    __a     (					self    ) ->      Dict:





								"""simple docstring"""


								self.accelerator.wait_for_everyone()
								with self.accelerator.autocast():
															for param in self.model.parameters():
																						lowercase__  :	List[str]        =							self.accelerator.reduce(param.data	,				reduction="mean"    )





import hashlib
import importlib.util
import json
import os
import pathlib
from types import ModuleType

import pytest
import requests

__a  :		str		     =   pathlib.Path.cwd().joinpath('''project_euler''')
__a  :		Tuple		     =   pathlib.Path.cwd().joinpath(
    '''scripts''', '''project_euler_answers.json'''
)

with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
						__a  :		dict[str, str]		     =   json.load(file_handle)
def  snake_case_					(		SCREAMING_SNAKE_CASE_    )      ->			ModuleType:
							lowercase__  :	List[str]        =							importlib.util.spec_from_file_location(file_path.name    ,str(SCREAMING_SNAKE_CASE_    )    )
							lowercase__  :	int        =							importlib.util.module_from_spec(SCREAMING_SNAKE_CASE_    )  # type: ignore
							spec.loader.exec_module(SCREAMING_SNAKE_CASE_    )  # type: ignore
							return module
def  snake_case_					(		)      ->			list[pathlib.Path]:
							lowercase__  :	List[str]        =							[]
							for problem_dir_path in PROJECT_EULER_DIR_PATH.iterdir():
														if problem_dir_path.is_file() or problem_dir_path.name.startswith("_"    ):
																					continue
														for file_path in problem_dir_path.iterdir():
																					if file_path.suffix != ".py" or file_path.name.startswith(("_", "test")    ):
																												continue
																					solution_file_paths.append(SCREAMING_SNAKE_CASE_    )
							return solution_file_paths
def  snake_case_					(		)      ->			str:
							with open(os.environ["GITHUB_EVENT_PATH"]    ) as file:
														lowercase__  :	str        =							json.load(SCREAMING_SNAKE_CASE_    )
							return event["pull_request"]["url"] + "/files"
def  snake_case_					(		)      ->			list[pathlib.Path]:
							lowercase__  :	Optional[Any]        =							[]
							lowercase__  :	Dict        =							{
							    "Accept": "application/vnd.github.v3+json",
							    "Authorization": "token " + os.environ["GITHUB_TOKEN"],
							}
							lowercase__  :	Union[str, Any]        =							requests.get(get_files_url()    ,headers=SCREAMING_SNAKE_CASE_    ).json()
							for file in files:
														lowercase__  :	Optional[Any]        =							pathlib.Path.cwd().joinpath(file["filename"]    )
														if (
														    filepath.suffix != ".py"
														    or filepath.name.startswith(("_", "test")    )
														    or not filepath.name.startswith("sol"    )
														):
																					continue
														solution_file_paths.append(SCREAMING_SNAKE_CASE_    )
							return solution_file_paths
def  snake_case_					(		)      ->			list[pathlib.Path]:
							if os.environ.get("CI"    ) and os.environ.get("GITHUB_EVENT_NAME"    ) == "pull_request":
														# Return only if there are any, otherwise default to all solutions
														if filepaths := added_solution_file_path():
																					return filepaths
							return all_solution_file_paths()




@pytest.mark.parametrize(
    "solution_path"    ,collect_solution_file_paths()    ,ids=lambda SCREAMING_SNAKE_CASE_    : F"""{path.parent.name}/{path.name}"""    ,)
def  snake_case_					(		SCREAMING_SNAKE_CASE_    )      ->			None:
							lowercase__  :	str        =							solution_path.parent.name[8:].zfill(3    )
							lowercase__  :	str        =							PROBLEM_ANSWERS[problem_number]
							lowercase__  :	Optional[Any]        =							convert_path_to_module(SCREAMING_SNAKE_CASE_    )
							lowercase__  :	str        =							str(solution_module.solution()    )  # type: ignore
							lowercase__  :	List[str]        =							hashlib.shaaaa(answer.encode()    ).hexdigest()
							assert (
							    answer == expected
							), F"""Expected solution to {problem_number} to have hash {expected}, got {answer}"""