class_docstr: Object class prediction network.
code: def _conv_bn_act(self, image, i, level_id, training):
      conv_op = self.conv_ops[i]
      bn = self.bns[i][level_id]
      act_type = self.act_type
  
      @utils.recompute_grad(self.grad_checkpoint)
      def _call(image):
          original_image = image
          image = conv_op(image)
          image = bn(image, training=training)
          if self.act_type:
              image = utils.activation_fn(image, act_type)
          if i > 0 and self.survival_prob:
              image = utils.drop_connect(
                  image, training, self.survival_prob
              )
              image = image + original_image
          return image
  
      return _call(image)
  
imports: import functools
  from absl import logging
  import numpy
  import tensorflow
  import utils
  from .None import fpn_configs
label_desc: Use image node_id 2 for calling the ClassNet obj's underlying member method code with example usage: obj._conv_bn_act(image, i, level_id, training) and returns: _call, image