code: def load_checkpoint(
      self, config, checkpoint_path, eval=False, cache=False
  ):  # pylint: disable=unused-argument, redefined-builtin
      state = torch.load(
          checkpoint_path, map_location=torch.device("cpu")
      )
      self.load_state_dict(state["model"])
      if eval:
          self.eval()
          assert not self.training
          self.remove_weight_norm()
  
imports: import torch
  import torchaudio
  from torch import nn
  from torch.nn import Conv1d, ConvTranspose1d
  from torch.nn import functional
  from torch.nn.utils.parametrizations import weight_norm
  from torch.nn.utils.parametrize import remove_parametrizations
  from TTS.utils.io import load_fsspec
label_desc: Use image node_id 5 for calling the HifiganGenerator obj's underlying member method code with example usage: obj.load_checkpoint(config, checkpoint_path, eval, cache) without return types