code: def load_expanded_conv(
      econv, expand_params, depthwise_params, project_params
  ):
      if hasattr(econv, "expand"):
          assert expand_params is not None
          c_to_p = [(econv.expand.conv, econv.expand.bn, expand_params)]
      else:
          assert expand_params is None
          c_to_p = []
      c_to_p.extend(
          [
              (
                  econv.depthwise.conv,
                  econv.depthwise.bn,
                  depthwise_params,
              ),
              (econv.project.conv, econv.project.bn, project_params),
          ]
      )
  
      for conv, bn, params in c_to_p:
          init_conv_with_tf_weights(conv, params["weights"])
          init_bn_with_tf_params(
              bn,
              params["beta"],
              params["gamma"],
              params["moving_mean"],
              params["moving_variance"],
          )
  
file_path: chainercv/examples/mobilenet/tfckpt2npz.py
imports: import argparse
  import chainer
  import tensorflow
  from chainercv.links import MobileNetV2
label_desc: Use image node_id 1 for calling a global function with example usage: load_expanded_conv(econv, expand_params, depthwise_params, project_params) without return types