

"""simple docstring"""




import random
from typing import List, Optional, Union

import numpy as np
import torch

from ..state import AcceleratorState
from .constants import CUDA_DISTRIBUTED_TYPES
from .dataclasses import DistributedType, RNGType
from .imports import is_npu_available, is_tpu_available, is_xpu_available


if is_tpu_available(check_device=False):
      import torch_xla.core.xla_model as xm
def 					lowerCAmelCase  (   __UpperCamelCase							,      __UpperCamelCase = False ):
 '''simple docstring'''





 if device_specific:
  seed += AcceleratorState().process_index
 random.seed(__UpperCamelCase )
 np.random.seed(__UpperCamelCase )
 torch.manual_seed(__UpperCamelCase )
 if is_xpu_available():
  torch.xpu.manual_seed_all(__UpperCamelCase )
 elif is_npu_available():
  torch.npu.manual_seed_all(__UpperCamelCase )
 else:
  torch.cuda.manual_seed_all(__UpperCamelCase )
 # ^^ safe to call this function even if cuda is not available
 if is_tpu_available():
  xm.set_rng_state(__UpperCamelCase )
def 					lowerCAmelCase  (   __UpperCamelCase = None							,      __UpperCamelCase = None ):
 '''simple docstring'''





 if rng_type == RNGType.TORCH:
  UpperCAmelCase__   :					Union[str, Any]   				=   torch.get_rng_state()
 elif rng_type == RNGType.CUDA:
  UpperCAmelCase__   :					List[str]   				=   torch.cuda.get_rng_state()
 elif rng_type == RNGType.XLA:
  assert is_tpu_available(), "Can't synchronize XLA seeds on an environment without TPUs."
  UpperCAmelCase__   :					Any   				=   torch.tensor(xm.get_rng_state() )
 elif rng_type == RNGType.NPU:
  assert is_npu_available(), "Can't synchronize NPU seeds on an environment without NPUs."
  UpperCAmelCase__   :					Tuple   				=   torch.npu.get_rng_state()
 elif rng_type == RNGType.XPU:
  assert is_xpu_available(), "Can't synchronize XPU seeds on an environment without XPUs."
  UpperCAmelCase__   :					Union[str, Any]   				=   torch.xpu.get_rng_state()
 elif rng_type == RNGType.GENERATOR:
  assert generator is not None, "Need a generator to synchronize its seed."
  UpperCAmelCase__   :					List[str]   				=   generator.get_state()

 # Broadcast the rng state from device 0 to other devices
 UpperCAmelCase__   :					Optional[int]   				=   AcceleratorState()
 if state.distributed_type == DistributedType.TPU:
  UpperCAmelCase__   :					List[Any]   				=   rng_state.to(xm.xla_device() )
  xm.collective_broadcast([rng_state] )
  xm.mark_step()
  UpperCAmelCase__   :					Optional[Any]   				=   rng_state.cpu()
 elif (
     state.distributed_type in CUDA_DISTRIBUTED_TYPES
     or state.distributed_type == DistributedType.MULTI_NPU
     or state.distributed_type == DistributedType.MULTI_XPU
 ):
  UpperCAmelCase__   :					List[Any]   				=   rng_state.to(state.device )
  torch.distributed.broadcast(__UpperCamelCase							,      0 )
  UpperCAmelCase__   :					int   				=   rng_state.cpu()
 elif state.distributed_type == DistributedType.MULTI_CPU:
  torch.distributed.broadcast(__UpperCamelCase							,      0 )

 # Set the broadcast rng state
 if rng_type == RNGType.TORCH:
  torch.set_rng_state(__UpperCamelCase )
 elif rng_type == RNGType.CUDA:
  torch.cuda.set_rng_state(__UpperCamelCase )
 elif rng_type == RNGType.NPU:
  torch.npu.set_rng_state(__UpperCamelCase )
 elif rng_type == RNGType.XPU:
  torch.xpu.set_rng_state(__UpperCamelCase )
 elif rng_type == RNGType.XLA:
  xm.set_rng_state(rng_state.item() )
 elif rng_type == RNGType.GENERATOR:
  generator.set_state(__UpperCamelCase )




def 					lowerCAmelCase  (   __UpperCamelCase							,      __UpperCamelCase = None ):
 '''simple docstring'''





 for rng_type in rng_types:
  synchronize_rng_state(RNGType(__UpperCamelCase )							,      generator=__UpperCamelCase )








"""simple docstring"""




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

import pytest
import requests

__UpperCAmelCase	=			pathlib.Path.cwd().joinpath('project_euler')
__UpperCAmelCase	=			pathlib.Path.cwd().joinpath(
    'scripts', 'project_euler_answers.json'
)

with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
      __UpperCAmelCase	=			json.load(file_handle)
def 					lowerCAmelCase  (   __UpperCamelCase ):
 '''simple docstring'''





 UpperCAmelCase__   :					Dict   				=   importlib.util.spec_from_file_location(file_path.name							,      str(__UpperCamelCase ) )
 UpperCAmelCase__   :					Optional[Any]   				=   importlib.util.module_from_spec(__UpperCamelCase )  # type: ignore
 spec.loader.exec_module(__UpperCamelCase )  # type: ignore
 return module
def 					lowerCAmelCase  (   ):
 '''simple docstring'''





 UpperCAmelCase__   :					Dict   				=   []
 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(__UpperCamelCase )
 return solution_file_paths
def 					lowerCAmelCase  (   ):
 '''simple docstring'''





 with open(os.environ["""GITHUB_EVENT_PATH"""] ) as file:
  UpperCAmelCase__   :					List[Any]   				=   json.load(__UpperCamelCase )
 return event["pull_request"]["url"] + "/files"
def 					lowerCAmelCase  (   ):
 '''simple docstring'''





 UpperCAmelCase__   :					Tuple   				=   []
 UpperCAmelCase__   :					List[str]   				=   {
     """Accept""": """application/vnd.github.v3+json""",
     """Authorization""": """token """ + os.environ["""GITHUB_TOKEN"""],
 }
 UpperCAmelCase__   :					Tuple   				=   requests.get(get_files_url()							,      headers=__UpperCamelCase ).json()
 for file in files:
  UpperCAmelCase__   :					List[str]   				=   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(__UpperCamelCase )
 return solution_file_paths
def 					lowerCAmelCase  (   ):
 '''simple docstring'''





 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 __UpperCamelCase : F"{path.parent.name}/{path.name}"							,      )
def 					lowerCAmelCase  (   __UpperCamelCase ):
 '''simple docstring'''





 UpperCAmelCase__   :					str   				=   solution_path.parent.name[8:].zfill(3 )
 UpperCAmelCase__   :					str   				=   PROBLEM_ANSWERS[problem_number]
 UpperCAmelCase__   :					int   				=   convert_path_to_module(__UpperCamelCase )
 UpperCAmelCase__   :					str   				=   str(solution_module.solution() )  # type: ignore
 UpperCAmelCase__   :					Optional[Any]   				=   hashlib.shaaaa(answer.encode() ).hexdigest()
 assert (
     answer == expected
 ), F"Expected solution to {problem_number} to have hash {expected}, got {answer}"





