class_docstr: Regular classifier network for small-size images
  
  Args:
      input_size (int, optional): the dimension of the final feature vector. Defaults to 128.
      n_class (int, optional): the number of classes. Defaults to 10.
class_docstr_tok: ["Regular","classifier","network","for","small-size","images","Args",":","input_size","(","int",",","optional",")",":","the","dimension","of","the","final","feature","vector",".","Defaults","to","128.","n_class","(","int",",","optional",")",":","the","number","of","classes",".","Defaults","to","10","."]
code: def n_classes(self):
      return self._n_classes
  
imports: import torch
  import torch.nn
  from kale.embed.video_i3d import Unit3D
label_desc: Use image node_id 2 for calling the ClassNetSmallImage obj's underlying member method code with example usage: obj.n_classes() and returns: self