code: def get_model(config):
      class SimpleModel(gluon.nn.HybridBlock):
          def __init__(self, **kwargs):
              super(SimpleModel, self).__init__(**kwargs)
              self.fc1 = nn.Dense(20)
              self.fc2 = nn.Dense(40)
              self.fc3 = nn.Dense(10)
  
          def hybrid_forward(self, F, x1, x2):
              y1 = self.fc1(x1)
              y2 = self.fc2(x2)
              y = F.concat(y1, y2, dim=1)
              return self.fc3(y)
  
      net = SimpleModel()
      net.initialize(
          mx.init.Xavier(rnd_type="gaussian"),
          ctx=[mx.cpu()],
          force_reinit=True,
      )
      return net
  
file_path: BigDL/python/orca/test/bigdl/orca/learn/ray/mxnet/test_mxnet_gluon_multiple_input.py
imports: from unittest import TestCase
  import numpy
  import pytest
  import mxnet
  from mxnet import gluon
  from mxnet.gluon import nn
  from bigdl.orca.learn.mxnet import Estimator, create_config
label_desc: Use image node_id 3 for calling a global function with example usage: get_model(config) and returns: net, self