code: def get_symbol(num_classes=1000, **kwargs):
      data = mx.sym.Variable("data")
      conv1 = ConvFactory(
          data,
          64,
          kernel=(7, 7),
          stride=(2, 2),
          pad=(3, 3),
          name="conv1",
      )
      pool1 = mx.sym.Pooling(
          conv1, kernel=(3, 3), stride=(2, 2), pool_type="max"
      )
      conv2 = ConvFactory(
          pool1, 64, kernel=(1, 1), stride=(1, 1), name="conv2"
      )
      conv3 = ConvFactory(
          conv2,
          192,
          kernel=(3, 3),
          stride=(1, 1),
          pad=(1, 1),
          name="conv3",
      )
      pool3 = mx.sym.Pooling(
          conv3, kernel=(3, 3), stride=(2, 2), pool_type="max"
      )
  
      in3a = InceptionFactory(
          pool3, 64, 96, 128, 16, 32, "max", 32, name="in3a"
      )
      in3b = InceptionFactory(
          in3a, 128, 128, 192, 32, 96, "max", 64, name="in3b"
      )
      pool4 = mx.sym.Pooling(
          in3b, kernel=(3, 3), stride=(2, 2), pool_type="max"
      )
      in4a = InceptionFactory(
          pool4, 192, 96, 208, 16, 48, "max", 64, name="in4a"
      )
      in4b = InceptionFactory(
          in4a, 160, 112, 224, 24, 64, "max", 64, name="in4b"
      )
      in4c = InceptionFactory(
          in4b, 128, 128, 256, 24, 64, "max", 64, name="in4c"
      )
      in4d = InceptionFactory(
          in4c, 112, 144, 288, 32, 64, "max", 64, name="in4d"
      )
      in4e = InceptionFactory(
          in4d, 256, 160, 320, 32, 128, "max", 128, name="in4e"
      )
      pool5 = mx.sym.Pooling(
          in4e, kernel=(3, 3), stride=(2, 2), pool_type="max"
      )
      in5a = InceptionFactory(
          pool5, 256, 160, 320, 32, 128, "max", 128, name="in5a"
      )
      in5b = InceptionFactory(
          in5a, 384, 192, 384, 48, 128, "max", 128, name="in5b"
      )
      pool6 = mx.sym.Pooling(
          in5b,
          kernel=(7, 7),
          stride=(1, 1),
          global_pool=True,
          pool_type="avg",
      )
      flatten = mx.sym.Flatten(data=pool6)
      fc1 = mx.sym.FullyConnected(data=flatten, num_hidden=num_classes)
      softmax = mx.symbol.SoftmaxOutput(data=fc1, name="softmax")
      return softmax
  
imports: import mxnet
label_desc: Use image node_id 3 for calling a global function with example usage: get_symbol(num_classes) and returns: softmax