class_docstr: A feature extractor for small 32x32 images (e.g. CIFAR, MNIST) that outputs a feature vector of length 128.
  
  Args:
      num_channels (int): the number of input channels (default=3).
      kernel_size (int): the size of the convolution kernel (default=5).
  
  Examples::
      >>> feature_network = SmallCNNFeature(num_channels)
code: def output_size(self):
      return self._out_features
  
imports: import torch.nn
  from torch.nn import functional
  from torchvision import models
label_desc: Use image node_id 3 for calling the SmallCNNFeature obj's underlying member method code with example usage: obj.output_size() and returns: self