

"""simple docstring"""




import inspect
import os
import unittest

import torch

import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment


class 			A						(							unittest.TestCase			):







    """simple docstring"""





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





        '''simple docstring'''







        A__   				=       inspect.getfile(accelerate.test_utils		)
        A__   				=       os.path.sep.join(mod_file.split(os.path.sep		)[:-1] + ['scripts', 'test_script.py']		)
        A__   				=       os.path.sep.join(
            mod_file.split(os.path.sep		)[:-1] + ['scripts', 'test_distributed_data_loop.py']		)
        A__   				=       os.path.sep.join(mod_file.split(os.path.sep		)[:-1] + ['scripts', 'test_ops.py']		)


    @require_multi_gpu
    def 						snake_case__					(				self			:	str		)->   int:





        '''simple docstring'''







        print(F'Found {torch.cuda.device_count()} devices.'		)
        A__   				=       ['torchrun', F'--nproc_per_node={torch.cuda.device_count()}', self.test_file_path]
        with patch_environment(omp_num_threads=1		):
            execute_subprocess_async(lowercase_,env=os.environ.copy()		)


    @require_multi_gpu
    def 						snake_case__					(				self			:	Optional[int]		)->   List[Any]:





        '''simple docstring'''







        print(F'Found {torch.cuda.device_count()} devices.'		)
        A__   				=       ['torchrun', F'--nproc_per_node={torch.cuda.device_count()}', self.operation_file_path]
        print(F'Command: {cmd}'		)
        with patch_environment(omp_num_threads=1		):
            execute_subprocess_async(lowercase_,env=os.environ.copy()		)


    @require_multi_gpu
    def 						snake_case__					(				self			:	Dict		)->   Union[str, Any]:





        '''simple docstring'''







        A__   				=       ['torchrun', F'--nproc_per_node={torch.cuda.device_count()}', inspect.getfile(self.__class__		)]
        with patch_environment(omp_num_threads=1		):
            execute_subprocess_async(lowercase_,env=os.environ.copy()		)


    @require_multi_gpu
    def 						snake_case__					(				self			:	List[str]		)->   Tuple:





        '''simple docstring'''







        print(F'Found {torch.cuda.device_count()} devices, using 2 devices only'		)
        A__   				=       ['torchrun', F'--nproc_per_node={torch.cuda.device_count()}', self.data_loop_file_path]
        with patch_environment(omp_num_threads=1,cuda_visible_devices='0,1'		):
            execute_subprocess_async(lowercase_,env=os.environ.copy()		)


if __name__ == "__main__":
     lowercase_			=  Accelerator()
     lowercase_			=  (accelerator.state.process_index + 2, 10)
     lowercase_			=  torch.randint(0, 10, shape).to(accelerator.device)

     lowercase_			=  ""

     lowercase_			=  accelerator.pad_across_processes(tensor)
     if tensora.shape[0] != accelerator.state.num_processes + 1:
          error_msg += f"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
     if not torch.equal(tensora[: accelerator.state.process_index + 2], tensor):
          error_msg += "Tensors have different values."
     if not torch.all(tensora[accelerator.state.process_index + 2 :] == 0):
          error_msg += "Padding was not done with the right value (0)."

     lowercase_			=  accelerator.pad_across_processes(tensor, pad_first=True)
     if tensora.shape[0] != accelerator.state.num_processes + 1:
          error_msg += f"Found shape {tensora.shape} but should have {accelerator.state.num_processes + 1} at dim 0."
     lowercase_			=  accelerator.state.num_processes - accelerator.state.process_index - 1
     if not torch.equal(tensora[index:], tensor):
          error_msg += "Tensors have different values."
     if not torch.all(tensora[:index] == 0):
          error_msg += "Padding was not done with the right value (0)."

     # Raise error at the end to make sure we don't stop at the first failure.
     if len(error_msg) > 0:
          raise ValueError(error_msg)




from __future__ import annotations

from typing import Any
def 						_snake_case(   SCREAMING_SNAKE_CASE__      :     list				)							->				int:





    '''simple docstring'''






    if not postfix_notation:
        return 0

    A__   				=       {'+', '-', '*', '/'}
    A__   				=       []

    for token in postfix_notation:
        if token in operations:
            A__				,						A__   				=       stack.pop(), stack.pop()
            if token == "+":
                stack.append(a + b				)
            elif token == "-":
                stack.append(a - b				)
            elif token == "*":
                stack.append(a * b				)
            else:
                if a * b < 0 and a % b != 0:
                    stack.append(a // b + 1				)
                else:
                    stack.append(a // b				)
        else:
            stack.append(int(SCREAMING_SNAKE_CASE__				)				)

    return stack.pop()


if __name__ == "__main__":
     import doctest

     doctest.testmod()

