code: def convert_keras_model(
      model_keras,
      model_objax,
      num_blocks: list,
      include_top: bool = True,
  ):
      """Converts Keras implementation of ResNetV2 into Objax."""
      convert_conv_or_linear_layer(
          model_keras.get_layer("conv1_conv"), model_objax[0]
      )
      for b, j in enumerate(num_blocks):
          for i in range(j):
              convert_resblock(
                  [
                      layer
                      for layer in model_keras.layers
                      if layer.name.startswith(
                          "conv{}_block{}".format(b + 2, i + 1)
                      )
                  ],
                  model_objax[b + 3][i],
              )
      convert_bn_layer(model_keras.get_layer("post_bn"), model_objax[7])
      if include_top:
          convert_conv_or_linear_layer(
              model_keras.get_layer("predictions"), model_objax[10]
          )
  
imports: import functools
  from typing import Callable, Sequence, Union, Optional
  from jax import numpy
  import objax
  from objax.constants import ConvPadding
  from objax.nn import Conv2D
  from objax.typing import JaxArray, ConvPaddingInt
label_desc: Use image node_id 5 for calling a global function with example usage: convert_keras_model(model_keras, model_objax, num_blocks, include_top) without return types