code: def test_with_loader(self):
      p = torch.tensor([2.0, 1.0, 10.0])
      training_steps = 2
  
      model = Net(p)
      optim = torch.optim.SGD(model.parameters(), lr=0.01)
      test_var = {"loaded": False}
  
      def custom_loader(state):
          state[torchbearer.X], state[torchbearer.Y_TRUE] = None, None
          test_var["loaded"] = True
  
      trial = (
          torchbearer.Trial(
              model,
              optim,
              loss,
              callbacks=[
                  torchbearer.callbacks.MostRecent(filepath="test.pt")
              ],
          )
          .for_train_steps(training_steps)
          .for_val_steps(1)
      )
      trial.with_loader(custom_loader)
      self.assertTrue(not test_var["loaded"])
      trial.run(1)
      self.assertTrue(test_var["loaded"])
  
      import os
  
      os.remove("test.pt")
  
imports: import unittest
  import torch
  from torch.nn import Module, Linear
  import torch.nn.init
  import torchbearer
  from torchbearer import callbacks
label_desc: Use image node_id 5 for calling the TestEndToEnd obj's underlying member method code with example usage: obj.test_with_loader() without return types