class_docstr: Progressive Neural Network.
  
  The model assumes that each experience is a separate task.
  Multiple experiences with the same task label or multiple task labels
  within the same experience will result in a runtime error.
docstr: Forward.
  
  :param x:
  :param task_label:
  :return:
docstr_tok: ["Forward",".",":","param","x",":",":","param","task_label",":",":","return",":"]
code: def forward_single_task(self, x, task_label):
      """Forward.
  
      :param x:
      :param task_label:
      :return:
      """
      x = x.contiguous()
      x = x.view(x.size(0), self.in_features)
  
      num_columns = self.layers[0].num_columns
      col_idx = self.layers[-1].task_to_module_idx[task_label]
  
      x = [x for _ in range(num_columns)]
      for lay in self.layers:
          x = [F.relu(el) for el in lay(x, task_label)]
      return self.classifier(x[col_idx], task_label)
  
imports: import torch
  import torch.nn.functional
  from torch import nn
  from avalanche.benchmarks.utils.flat_data import ConstantSequence
  from avalanche.models import MultiTaskModule
  from avalanche.models import MultiHeadClassifier
  from avalanche.benchmarks.scenarios import CLExperience
label_desc: Use image node_id 2 for calling the PNN obj's underlying member method code with example usage: obj.forward_single_task(x, task_label) and returns: self