class_docstr: A generic TS Transformer LightningMoudle for light-weight HPO.
docstr: Define a single test step.
docstr_tok: ["Define","a","single","test","step","."]
code: def predict_step(self, batch, batch_idx):
      """Define a single test step."""
      y_hat = self(*batch)
      return y_hat
  
imports: from bigdl.nano.pytorch.lightning import LightningModule
  from bigdl.nano.utils.common import invalidInputError
  from typing import List
  import pytorch_lightning
  from torchmetrics.metric import Metric
  from torch.optim.lr_scheduler import _LRScheduler
  import bigdl.nano.automl.hpo
  import warnings
  import torch
  import inspect
  from torch import nn, Tensor, fx
  from torch.utils.data import TensorDataset, DataLoader
  from bigdl.nano.automl.hpo.space import Space
label_desc: Use image node_id 7 for calling the GenericTSTransformerLightningModule obj's underlying member method code with example usage: obj.predict_step(batch, batch_idx) and returns: y_hat