def METHOD_NAME(conv_name, original_tensor_dict):
  # conv kernel shape HWCN
  conv_kernel = original_tensor_dict[conv_name]
  beta_name, gamma_name, mean_name, variance_name = infer_bn_names(conv_name)
  beta = original_tensor_dict[beta_name]
  gamma = original_tensor_dict[gamma_name]
  mean = original_tensor_dict[mean_name]
  variance = original_tensor_dict[variance_name]
  # print(type(conv_kernel))
  # print(type(beta))
  tf.logging.debug(conv_kernel)
  tf.logging.debug(beta)
  tf.logging.debug(gamma)
  tf.logging.debug(mean)
  tf.logging.debug(variance)
  # TODO: compute merged W and b
  return