How do you get the name of the tensorflow output nodes in a Keras Model?

When developing deep learning models with Keras, you may need to know the output node names, especially when deploying the model to production environments or using other TensorFlow tools such as TensorFlow Serving and TensorFlow Lite.

The steps to obtain the output node names are as follows:

1. Build the model: Ensure that your model is correctly built and compiled. This is the foundation for obtaining the output node names.

2. Use the summary() function: Calling model.summary() prints detailed information about all layers of the model, including their names. However, it does not directly display the TensorFlow output node names.

3. Inspect the model's output tensors: Using model.output directly retrieves the model's output tensors. Typically, this helps you understand how the output nodes are constructed.

4. Use keras.backend to obtain node names:

   • First, import the Keras backend module, typically done as:

     python
     from keras import backend as K

   • Then, if your model is a Sequential model, you can obtain the output node name with:

     python
     output_node_name = model.output.op.name
     print("Output node name is:", output_node_name)

   • If your model is a Functional API model, which may have multiple outputs, you can do:

     python
     output_node_names = [output.op.name for output in model.outputs]
     print("Output node names list:", output_node_names)

5. Practical Example:

   • Assume we have a simple Sequential model:

     python
     from keras.models import Sequential
     from keras.layers import Dense
     
     model = Sequential([
         Dense(64, activation='relu', input_shape=(32,)),
         Dense(1, activation='sigmoid')
     ])
     model.compile(optimizer='adam', loss='binary_crossentropy')

   • Using the above method to obtain the output node name:

     python
     from keras import backend as K
     
     output_node_name = model.output.op.name
     print("Output node name is:", output_node_name)

By following these steps, you can successfully obtain the TensorFlow output node names in Keras models, which is very helpful for further usage and deployment of the model.