class_docstr: Network-in-Network example model.
code: def __call__(self, x, t):
      h = F.max_pooling_2d(F.relu(self.mlpconv1(x)), 3, stride=2)
      h = F.max_pooling_2d(F.relu(self.mlpconv2(h)), 3, stride=2)
      h = F.max_pooling_2d(F.relu(self.mlpconv3(h)), 3, stride=2)
      h = self.mlpconv4(F.dropout(h))
      h = F.reshape(F.average_pooling_2d(h, 6), (len(x), 1000))
  
      loss = F.softmax_cross_entropy(h, t)
      chainer.report({"loss": loss, "accuracy": F.accuracy(h, t)}, self)
      return loss
  
file_path: chainer/examples/chainermn/imagenet/models/nin.py
imports: import chainer
  import chainer.functions
  import chainer.initializers
  import chainer.links
label_desc: Use image node_id 2 for calling the NIN obj's underlying member method code with example usage: obj.__call__(x, t) and returns: loss