old_contents: # Copyright The PyTorch Lightning team.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  """General utilities"""
  import importlib
  import platform
  from distutils.version import LooseVersion
  
  import pkg_resources
  import torch
  
  
  def _module_available(module_path: str) -> bool:
      """Testing if given module is avalaible in your env
  
      >>> _module_available('os')
      True
      >>> _module_available('bla.bla')
      False
      """
      # todo: find a better way than try / except
      try:
          mods = module_path.split('.')
          assert mods, 'nothing given to test'
          # it has to be tested as per partets
          for i in range(len(mods)):
              module_path = '.'.join(mods[:i + 1])
              if importlib.util.find_spec(module_path) is None:
                  return False
          return True
      except AttributeError:
          return False
  
  
  _APEX_AVAILABLE = _module_available("apex.amp")
  _NATIVE_AMP_AVAILABLE = _module_available("torch.cuda.amp") and hasattr(torch.cuda.amp, "autocast")
  _OMEGACONF_AVAILABLE = _module_available("omegaconf")
  _HYDRA_AVAILABLE = _module_available("hydra")
  _HYDRA_EXPERIMENTAL_AVAILABLE = _module_available("hydra.experimental")
  _HOROVOD_AVAILABLE = _module_available("horovod.torch")
  _TORCHTEXT_AVAILABLE = _module_available("torchtext")
  _XLA_AVAILABLE = _module_available("torch_xla")
  _FAIRSCALE_AVAILABLE = platform.system() != 'Windows' and _module_available('fairscale.nn.data_parallel')
  _RPC_AVAILABLE = platform.system() != 'Windows' and _module_available('torch.distributed.rpc')
  _GROUP_AVAILABLE = platform.system() != 'Windows' and _module_available('torch.distributed.group')
  _FAIRSCALE_PIPE_AVAILABLE = _FAIRSCALE_AVAILABLE and LooseVersion(
      torch.__version__
  ) >= LooseVersion("1.6.0") and LooseVersion(pkg_resources.get_distribution('fairscale').version
                                              ) <= LooseVersion("0.1.3")
  _BOLTS_AVAILABLE = _module_available('pl_bolts')
  _TORCHVISION_AVAILABLE = _module_available('torchvision')
  
new_contents: # Copyright The PyTorch Lightning team.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  """General utilities"""
  import platform
  from distutils.version import LooseVersion
  from importlib.util import find_spec
  
  import pkg_resources
  import torch
  
  
  def _module_available(module_path: str) -> bool:
      """
      Check if a path is available in your environment
  
      >>> _module_available('os')
      True
      >>> _module_available('bla.bla')
      False
      """
      try:
          return find_spec(module_path) is not None
      except AttributeError:
          # Python 3.6
          return False
      except ModuleNotFoundError:
          # Python 3.7+
          return False
  
  
  def _get_version(package: str) -> LooseVersion:
      return LooseVersion(pkg_resources.get_distribution(package).version)
  
  
  _IS_WINDOWS = platform.system() == "Windows"
  _TORCH_GREATER_EQUAL_1_6 = _get_version("torch") >= LooseVersion("1.6.0")
  
  _APEX_AVAILABLE = _module_available("apex.amp")
  _BOLTS_AVAILABLE = _module_available('pl_bolts')
  _FAIRSCALE_AVAILABLE = not _IS_WINDOWS and _module_available('fairscale.nn.data_parallel')
  _FAIRSCALE_PIPE_AVAILABLE = (
      _FAIRSCALE_AVAILABLE and _TORCH_GREATER_EQUAL_1_6 and _get_version('fairscale') <= LooseVersion("0.1.3")
  )
  _GROUP_AVAILABLE = not _IS_WINDOWS and _module_available('torch.distributed.group')
  _HOROVOD_AVAILABLE = _module_available("horovod.torch")
  _HYDRA_AVAILABLE = _module_available("hydra")
  _HYDRA_EXPERIMENTAL_AVAILABLE = _module_available("hydra.experimental")
  _NATIVE_AMP_AVAILABLE = _module_available("torch.cuda.amp") and hasattr(torch.cuda.amp, "autocast")
  _OMEGACONF_AVAILABLE = _module_available("omegaconf")
  _RPC_AVAILABLE = not _IS_WINDOWS and _module_available('torch.distributed.rpc')
  _TORCHTEXT_AVAILABLE = _module_available("torchtext")
  _TORCHVISION_AVAILABLE = _module_available('torchvision')
  _XLA_AVAILABLE = _module_available("torch_xla")
  
subject: Refactor utilities/imports.py (#5874)