class_docstr: Abstract base class for deep learning networks using torch.nn.
class_docstr_tok: ["Abstract","base","class","for","deep","learning","networks","using","torch.nn","."]
docstr: Get y_true values for validation.
docstr_tok: ["Get","y_true","values","for","validation","."]
code: def get_y_true(self, y):
      """Get y_true values for validation."""
      dataloader = self.build_pytorch_pred_dataloader(y)
      y_true = [y.flatten().numpy() for _, y in dataloader]
      return np.concatenate(y_true, axis=0)
  
imports: from abc import ABC, abstractmethod
  import numpy
  import pandas
  from sktime.base import BaseObject
  from sktime.forecasting.base import BaseForecaster
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 6 for calling the BaseDeepNetworkPyTorch obj's underlying member method code with example usage: obj.get_y_true(y) and returns: np