code: def __init__(
      self,
  ):
      super(Torch_Model, self).__init__()
      self.convs = nn.Sequential(
          nn.Conv2d(1, 32, 3),
          nn.ReLU(),
          nn.Conv2d(32, 64, 3),
          nn.ReLU(),
          nn.MaxPool2d(2),
          nn.Dropout(0.25),
      )
      self.fcs = nn.Sequential(
          nn.Linear(12 * 12 * 64, 128),
          nn.ReLU(),
          nn.Dropout(0.5),
          nn.Linear(128, 10),
      )
  
file_path: modAL/examples/pytorch_integration.py
imports: import numpy
  import torch
  from modAL.models import ActiveLearner
  from skorch import NeuralNetClassifier
  from torch import nn
  from torch.utils.data import DataLoader
  from torchvision.datasets import MNIST
  from torchvision.transforms import ToTensor
label_desc: Use image node_id 1 to create a new Torch_Model object from inherited base classes: nn with example: obj = Torch_Model()