code: def call(self, inputs, training=False, **kwargs):
      x = self.conv1(inputs)
      x = self.bn1(x, training=training)
      x = self.relu1(x)
      x = self.maxpool1(x)
  
      x = self.block1(x, training=training)
      x = self.block2(x, training=training)
      x = self.block3(x, training=training)
      x = self.block4(x, training=training)
  
      if self.include_top:
          x = self.avgpool(x)
          x = self.fc(x)
          x = self.softmax(x)
  
      return x
  
file_path: deep-learning-for-image-processing/tensorflow_classification/Test5_resnet/subclassed_model.py
imports: from tensorflow.keras import layers, Model, Sequential
label_desc: Use image node_id 2 for calling the ResNet obj's underlying member method code with example usage: obj.call(inputs, training) and returns: x