class_docstr: Spatial Pyramid Pooling in Deep Convolutional Networks
class_docstr_tok: ["Spatial","Pyramid","Pooling","in","Deep","Convolutional","Networks"]
code: def __init__(self, kernel_size1, kernel_size2, kernel_size3):
      super().__init__()
      self.pool1 = nn.MaxPool2d(
          kernel_size1, stride=1, padding=kernel_size1 // 2
      )
      self.pool2 = nn.MaxPool2d(
          kernel_size2, stride=1, padding=kernel_size2 // 2
      )
      self.pool3 = nn.MaxPool2d(
          kernel_size3, stride=1, padding=kernel_size3 // 2
      )
  
imports: import torch
  from torch import nn
label_desc: Use image node_id 1 to create a new SPP object from inherited base classes: nn with example: obj = SPP(kernel_size1, kernel_size2, kernel_size3)