class_docstr: Spatial Pyramid Pooling in Deep Convolutional Networks
class_docstr_tok: ["Spatial","Pyramid","Pooling","in","Deep","Convolutional","Networks"]
code: def forward(self, x):
      x1 = self.pool1(x)
      x2 = self.pool2(x)
      x3 = self.pool3(x)
      return torch.cat([x, x1, x2, x3], dim=1)
  
imports: import torch
  from torch import nn
label_desc: Use image node_id 2 for calling the SPP obj's underlying member method code with example usage: obj.forward(x) and returns: torch