





import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment





class 					lowerCAmelCase							(   unittest.TestCase					):







  def   UpperCAmelCase     (			self  :int					):






     '''simple docstring'''





     lowercase__    =  inspect.getfile(accelerate.test_utils					)
     lowercase__    =  os.path.sep.join(mod_file.split(os.path.sep					)[:-1] + ["scripts", "test_sync.py"]					)







  @require_cpu
  def   UpperCAmelCase     (			self  :Union[str, Any]					):






     '''simple docstring'''





     debug_launcher(test_sync.main    ,							num_processes=1					)







  @require_cpu
  def   UpperCAmelCase     (			self  :List[str]					):






     '''simple docstring'''





     debug_launcher(test_sync.main					)







  @require_single_gpu
  def   UpperCAmelCase     (			self  :List[str]					):






     '''simple docstring'''





     test_sync.main()







  @require_multi_gpu
  def   UpperCAmelCase     (			self  :List[Any]					):






     '''simple docstring'''





     print(f'''Found {torch.cuda.device_count()} devices.'''					)
     lowercase__    =  ["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()					)













from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_snake_case				= {"""configuration_regnet""": ["""REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RegNetConfig"""]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _snake_case				= [
      """REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """RegNetForImageClassification""",
      """RegNetModel""",
      """RegNetPreTrainedModel""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _snake_case				= [
      """TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """TFRegNetForImageClassification""",
      """TFRegNetModel""",
      """TFRegNetPreTrainedModel""",
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _snake_case				= [
      """FlaxRegNetForImageClassification""",
      """FlaxRegNetModel""",
      """FlaxRegNetPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_regnet import REGNET_PRETRAINED_CONFIG_ARCHIVE_MAP, RegNetConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_regnet import (
        REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        RegNetForImageClassification,
        RegNetModel,
        RegNetPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_regnet import (
        TF_REGNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFRegNetForImageClassification,
        TFRegNetModel,
        TFRegNetPreTrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_regnet import (
        FlaxRegNetForImageClassification,
        FlaxRegNetModel,
        FlaxRegNetPreTrainedModel,
    )


else:
  import sys

  _snake_case				= _LazyModule(__name__, globals()["""__file__"""], _import_structure)






