class_docstr: LightningModule wrapper over WaveNet.
  
  Parameters
  ----------
  model_kwargs
      Keyword arguments to pass to WaveNet.
  lr, optional
      Learning rate, by default 1e-3
  weight_decay, optional
      Weight decay, by default 1e-8
class_docstr_tok: ["LightningModule","wrapper","over","WaveNet",".","Parameters","--","--","--","--","--","model_kwargs","Keyword","arguments","to","pass","to","WaveNet",".","lr",",","optional","Learning","rate",",","by","default","1e-3","weight_decay",",","optional","Weight","decay",",","by","default","1e-8"]
code: def forward(self, *args, **kwargs):
      return self.model(*args, **kwargs)
  
file_path: gluonts/src/gluonts/torch/model/wavenet/lightning_module.py
imports: import lightning.pytorch
  import torch
  from gluonts.core.component import validated
  from .module import WaveNet
label_desc: Use image node_id 2 for calling the WaveNetLightningModule obj's underlying member method code with example usage: obj.forward() and returns: self