


'''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        __snake_case	(       unittest.TestCase):







    """simple docstring"""



    def __lowercase       (       self   :  Tuple		)       ->  List[str]:
      lowerCAmelCase_      :				Optional[Any]      =       inspect.getfile(accelerate.test_utils		)
      lowerCAmelCase_      :				Tuple      =       os.path.sep.join(mod_file.split(os.path.sep		)[:-1] + ["""scripts""", """test_script.py"""]		)
      lowerCAmelCase_      :				List[Any]      =       os.path.sep.join(
          mod_file.split(os.path.sep		)[:-1] + ["""scripts""", """test_distributed_data_loop.py"""]		)
      lowerCAmelCase_      :				Union[str, Any]      =       os.path.sep.join(mod_file.split(os.path.sep		)[:-1] + ["""scripts""", """test_ops.py"""]		)

    @require_multi_gpu
    def __lowercase       (       self   :  Optional[Any]		)       ->  str:
      print(F'Found {torch.cuda.device_count()} devices.'		)
      lowerCAmelCase_      :				Union[str, Any]      =       ["""torchrun""", F'--nproc_per_node={torch.cuda.device_count()}', self.test_file_path]
      with patch_environment(omp_num_threads=1		):
        execute_subprocess_async(lowerCamelCase   ,						env=os.environ.copy()		)

    @require_multi_gpu
    def __lowercase       (       self   :  str		)       ->  int:
      print(F'Found {torch.cuda.device_count()} devices.'		)
      lowerCAmelCase_      :				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(lowerCamelCase   ,						env=os.environ.copy()		)

    @require_multi_gpu
    def __lowercase       (       self   :  Dict		)       ->  List[str]:
      lowerCAmelCase_      :				Any      =       ["""torchrun""", F'--nproc_per_node={torch.cuda.device_count()}', inspect.getfile(self.__class__		)]
      with patch_environment(omp_num_threads=1		):
        execute_subprocess_async(lowerCamelCase   ,						env=os.environ.copy()		)





    @require_multi_gpu
    def __lowercase       (       self   :  Tuple		)       ->  Any:
      print(F'Found {torch.cuda.device_count()} devices, using 2 devices only'		)
      lowerCAmelCase_      :				List[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(lowerCamelCase   ,						env=os.environ.copy()		)


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

  __A :  Union[str, Any]    							=				""

  __A :  Dict    							=				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)."

  __A :  Tuple    							=				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."
  __A :  Dict    							=				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)







'''simple docstring'''






from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


try:
  if not (is_transformers_available() and is_torch_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
  from .notes_encoder import SpectrogramNotesEncoder
  from .continous_encoder import SpectrogramContEncoder
  from .pipeline_spectrogram_diffusion import (
      SpectrogramContEncoder,
      SpectrogramDiffusionPipeline,
      TaFilmDecoder,
  )

try:
  if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
  from .midi_utils import MidiProcessor



