class_docstr: Reduced ResNet 32
  
  This network architecture is an adaptation of ResNet for smaller
  input size. The number of blocks can be modified in this line by
  changing n=5 to n=3 for ResNet-20, and n=9 for ResNet-56.
  
  Implementation based on FACIL, as in:
  https://github.com/mmasana/FACIL/blob/master/src/networks/resnet32.py
class_docstr_tok: ["Reduced","ResNet","32","This","network","architecture","is","an","adaptation","of","ResNet","for","smaller","input","size",".","The","number","of","blocks","can","be","modified","in","this","line","by","changing","n=5","to","n=3","for","ResNet-20",",","and","n=9","for","ResNet-56",".","Implementation","based","on","FACIL",",","as","in",":","https",":","\/\/github.com\/mmasana\/FACIL\/blob\/master\/src\/networks\/resnet32.py"]
code: def forward(self, x):
      x = self.relu(self.bn1(self.conv1(x)))
      x = self.layer1(x)
      x = self.layer2(x)
      x = self.layer3(x)
      x = self.avgpool(x)
      x = x.view(x.size(0), -1)
      x = self.fc(x)
      return x
  
file_path: avalanche/avalanche/models/resnet32.py
imports: import torch.nn
label_desc: Use image node_id 3 for calling the ResNet obj's underlying member method code with example usage: obj.forward(x) and returns: x