

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):

  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     inspect.getfile(accelerate.test_utils					)
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     os.path.sep.join(mod_file.split(os.path.sep					)[:-1] + ['scripts', 'test_script.py']					)
        SCREAMING_SNAKE_CASE_				:  int           =     os.path.sep.join(
            mod_file.split(os.path.sep					)[:-1] + ['scripts', 'test_distributed_data_loop.py']					)
        SCREAMING_SNAKE_CASE_				:  List[Any]           =     os.path.sep.join(mod_file.split(os.path.sep					)[:-1] + ['scripts', 'test_ops.py']					)

  @require_multi_gpu
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        print(f"Found {torch.cuda.device_count()} devices."					)
        SCREAMING_SNAKE_CASE_				:  Dict           =     ['torchrun', f"--nproc_per_node={torch.cuda.device_count()}", self.test_file_path]
        with patch_environment(omp_num_threads=1					):
              execute_subprocess_async(_SCREAMING_SNAKE_CASE ,					env=os.environ.copy()					)

  @require_multi_gpu
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        print(f"Found {torch.cuda.device_count()} devices."					)
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     ['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(_SCREAMING_SNAKE_CASE ,					env=os.environ.copy()					)

  @require_multi_gpu
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Any           =     ['torchrun', f"--nproc_per_node={torch.cuda.device_count()}", inspect.getfile(self.__class__					)]
        with patch_environment(omp_num_threads=1					):
              execute_subprocess_async(_SCREAMING_SNAKE_CASE ,					env=os.environ.copy()					)



  @require_multi_gpu
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        print(f"Found {torch.cuda.device_count()} devices, using 2 devices only"					)
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     ['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(_SCREAMING_SNAKE_CASE ,					env=os.environ.copy()					)


if __name__ == "__main__":
    lowerCAmelCase     :   int						     =  Accelerator()
    lowerCAmelCase     :   List[Any]						     =  (accelerator.state.process_index + 2, 10)
    lowerCAmelCase     :   Dict						     =  torch.randint(0, 10, shape).to(accelerator.device)

    lowerCAmelCase     :   Optional[Any]						     =  ''

    lowerCAmelCase     :   Any						     =  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)."

    lowerCAmelCase     :   Optional[int]						     =  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."
    lowerCAmelCase     :   List[str]						     =  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)









lowerCAmelCase     :   Tuple						     =  {
    'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
    'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
    'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', 'U': '..-',
    'V': '...-', 'W': '.--', 'X': '-..-', 'Y': '-.--', 'Z': '--..', '1': '.----',
    '2': '..---', '3': '...--', '4': '....-', '5': '.....', '6': '-....', '7': '--...',
    '8': '---..', '9': '----.', '0': '-----', '&': '.-...', '@': '.--.-.',
    ':': '---...', ',': '--..--', '.': '.-.-.-', '\'': '.----.', '"': '.-..-.',
    '?': '..--..', '/': '-..-.', '=': '-...-', '+': '.-.-.', '-': '-....-',
    '(': '-.--.', ')': '-.--.-', '!': '-.-.--', ' ': '/'
}  # Exclamation mark is not in ITU-R recommendation
# fmt: on
lowerCAmelCase     :   Optional[int]						     =  {value: key for key, value in MORSE_CODE_DICT.items()}

def    A_  (							a  ):

      """simple docstring"""



      return " ".join(MORSE_CODE_DICT[char] for char in message.upper()  )

def    A_  (							a  ):

      """simple docstring"""



      return "".join(REVERSE_DICT[char] for char in message.split()  )

def    A_  (							):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  Tuple           =     'Morse code here!'
      print(a  )
      SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     encrypt(a  )
      print(a  )
      SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     decrypt(a  )
      print(a  )


if __name__ == "__main__":
    main()






