code: def test_keras_model_to_graph_def_functional_multi_inputs(self):
      expected_proto = """
              node {
                name: "model/main_input"
                attr {
                  key: "dtype"
                  value {
                    type: DT_INT32
                  }
                }
                attr {
                  key: "keras_class"
                  value {
                    s: "InputLayer"
                  }
                }
              }
              node {
                name: "model/embedding"
                input: "model/main_input"
                attr {
                  key: "dtype"
                  value {
                    type: DT_FLOAT
                  }
                }
                attr {
                  key: "keras_class"
                  value {
                    s: "Embedding"
                  }
                }
              }
              node {
                name: "model/simple_rnn"
                input: "model/embedding"
                attr {
                  key: "dtype"
                  value {
                    type: DT_FLOAT
                  }
                }
                attr {
                  key: "keras_class"
                  value {
                    s: "SimpleRNN"
                  }
                }
              }
              node {
                name: "model/aux_input"
                attr {
                  key: "dtype"
                  value {
                    type: DT_FLOAT
                  }
                }
                attr {
                  key: "keras_class"
                  value {
                    s: "InputLayer"
                  }
                }
              }
              node {
                name: "model/concatenate"
                input: "model/simple_rnn"
                input: "model/aux_input"
                attr {
                  key: "dtype"
                  value {
                    type: DT_FLOAT
                  }
                }
                attr {
                  key: "keras_class"
                  value {
                    s: "Concatenate"
                  }
                }
              }
              node {
                name: "model/dense"
                input: "model/concatenate"
                attr {
                  key: "dtype"
                  value {
                    type: DT_FLOAT
                  }
                }
                attr {
                  key: "keras_class"
                  value {
                    s: "Dense"
                  }
                }
              }
              node {
                name: "model/main_output"
                input: "model/dense"
                attr {
                  key: "dtype"
                  value {
                    type: DT_FLOAT
                  }
                }
                attr {
                  key: "keras_class"
                  value {
                    s: "Dense"
                  }
                }
              }
              node {
                name: "model/aux_output"
                input: "model/simple_rnn"
                attr {
                  key: "dtype"
                  value {
                    type: DT_FLOAT
                  }
                }
                attr {
                  key: "keras_class"
                  value {
                    s: "Dense"
                  }
                }
              }
          """
      main_input = keras.layers.Input(
          shape=(100,), dtype="int32", name="main_input"
      )
      x = keras.layers.Embedding(
          output_dim=512, input_dim=10000, input_length=100
      )(main_input)
      rnn_out = keras.layers.SimpleRNN(32)(x)
  
      auxiliary_output = keras.layers.Dense(
          1, activation="sigmoid", name="aux_output"
      )(rnn_out)
      auxiliary_input = keras.layers.Input(shape=(5,), name="aux_input")
  
      x = keras.layers.concatenate([rnn_out, auxiliary_input])
      x = keras.layers.Dense(64, activation="relu")(x)
  
      main_output = keras.layers.Dense(
          1, activation="sigmoid", name="main_output"
      )(x)
  
      model = keras.models.Model(
          inputs=[main_input, auxiliary_input],
          outputs=[main_output, auxiliary_output],
          name="model",
      )
  
      self.assertGraphDefToModel(expected_proto, model)
  
file_path: tensorboard/tensorboard/plugins/graph/keras_util_test.py
imports: import json
  import tensorflow
  from tensorboard.plugins.graph import keras_util
label_desc: Use image node_id 7 for calling the KerasUtilTest obj's underlying member method code with example usage: obj.test_keras_model_to_graph_def_functional_multi_inputs() without return types