class_docstr: ResNet V2 block with optional bottleneck.
class_docstr_tok: ["ResNet","V2","block","with","optional","bottleneck","."]
code: def __call__(self, inputs, is_training, test_local_stats):
      x = shortcut = inputs
  
      for i, (conv_i, bn_i) in enumerate(self.layers):
          x = bn_i(x, is_training, test_local_stats)
          x = jax.nn.relu(x)
          if i == 0 and self.use_projection:
              shortcut = self.proj_conv(x)
          x = conv_i(x)
  
      return x + shortcut
  
imports: from collections.abc import Mapping, Sequence
  from typing import Any, Optional, Union
  from haiku._src import basic
  from haiku._src import batch_norm
  from haiku._src import conv
  from haiku._src import module
  from haiku._src import pool
  import jax
  import jax.numpy
label_desc: Use image node_id 2 for calling the BlockV2 obj's underlying member method code with example usage: obj.__call__(inputs, is_training, test_local_stats) and returns: unknown