class_docstr: Abstract base class for deep learning networks using torch.nn.
docstr: Build PyTorch DataLoader for prediction.
docstr_tok: ["Build","PyTorch","DataLoader","for","prediction","."]
code: def build_pytorch_pred_dataloader(self, y, fh):
      """Build PyTorch DataLoader for prediction."""
      from torch.utils.data import DataLoader
  
      if self.custom_dataset_pred:
          if hasattr(
              self.custom_dataset_pred, "build_dataset"
          ) and callable(self.custom_dataset_pred.build_dataset):
              self.custom_dataset_train.build_dataset(y)
              dataset = self.custom_dataset_train
          else:
              raise NotImplementedError(
                  "Custom Dataset `build_dataset` method is not available. Please"
                  f"refer to the {self.__class__.__name__}.build_dataset"
                  "documentation."
              )
      else:
          dataset = PyTorchPredDataset(
              y=y[-self.network.seq_len :],
              seq_len=self.network.seq_len,
          )
  
      return DataLoader(
          dataset,
          self.batch_size,
      )
  
imports: from abc import ABC
  import numpy
  import pandas
  from sktime.forecasting.base import BaseForecaster
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 5 for calling the BaseDeepNetworkPyTorch obj's underlying member method code with example usage: obj.build_pytorch_pred_dataloader(y, fh) and returns: DataLoader