class_docstr: DeepChem Lightning Module to be used with Lightning trainer.
  
  TODO: Add dataloader, example code and fit, once datasetmodule
  is ready
  The lightning module is a wrapper over deepchem's torch model.
  This module directly works with pytorch lightning trainer
  which runs training for multiple epochs and also is responsible
  for setting up and training models on multiple GPUs.
  https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.core.LightningModule.html?highlight=LightningModule
  
  Notes
  -----
  This class requires PyTorch to be installed.
code: def configure_optimizers(self):
      return self.dc_model.optimizer._create_pytorch_optimizer(
          self.pt_model.parameters(),
      )
  
file_path: deepchem/deepchem/models/lightning/dc_lightning_module.py
imports: import torch
  import lightning
  from deepchem.models.torch_models import ModularTorchModel, TorchModel
label_desc: Use image node_id 2 for calling the DCLightningModule obj's underlying member method code with example usage: obj.configure_optimizers() and returns: self