class_docstr: Parallel WaveGAN Generator module.
docstr: Apply pre hook function before loading state dict.
docstr_tok: ["Apply","pre","hook","function","before","loading","state","dict","."]
code: def _load_state_dict_pre_hook(
      self,
      state_dict,
      prefix,
      local_metadata,
      strict,
      missing_keys,
      unexpected_keys,
      error_msgs,
  ):
      """Apply pre hook function before loading state dict."""
      keys = list(state_dict.keys())
      for k in keys:
          if "conv1x1_skip" in k.replace(prefix, ""):
              v_skip = state_dict.pop(k)
              v_out = state_dict[k.replace("skip", "out")]
              state_dict[k.replace("skip", "out")] = torch.cat(
                  [v_out, v_skip], dim=0
              )
  
imports: import logging
  import math
  from typing import Any, Dict, Optional
  import numpy
  import torch
  from espnet2.gan_tts.parallel_wavegan import upsample
  from espnet2.gan_tts.wavenet.residual_block import Conv1d, Conv1d1x1, ResidualBlock
label_desc: Use image node_id 8 for calling the ParallelWaveGANGenerator obj's underlying member method code with example usage: obj._load_state_dict_pre_hook(state_dict, prefix, local_metadata, strict, missing_keys, unexpected_keys, error_msgs) without return types