class_docstr: Bottleneck Block for a Resnet implementation.
class_docstr_tok: ["Bottleneck","Block","for","a","Resnet","implementation","."]
code: def __call__(self, inputs, is_training):
      net = inputs
      shortcut = inputs
  
      for i, (conv_i, bn_i) in enumerate(
          (
              (self._conv_0, self._bn_0),
              (self._conv_1, self._bn_1),
              (self._conv_2, self._bn_2),
          )
      ):
          net = bn_i(net, is_training=is_training)
          net = tf.nn.relu(net)
          if i == 0 and self._use_projection:
              shortcut = self._proj_conv(net)
          net = conv_i(net)
  
      return net + shortcut
  
imports: from typing import Mapping, Optional, Sequence, Union
  from sonnet.src import base
  from sonnet.src import batch_norm
  from sonnet.src import conv
  from sonnet.src import initializers
  from sonnet.src import linear
  from sonnet.src import pad
  import tensorflow
label_desc: Use image node_id 2 for calling the BottleNeckBlockV2 obj's underlying member method code with example usage: obj.__call__(inputs, is_training) and returns: unknown