Bring constant layers unconnected to the model into the model

[PINTO0309]

1. Content and background

• Constant

  • Bring Constant layers unconnected to the model into the model.

  • It is assumed that the -nuo option is specified because running onnxsim will remove constants from the ONNX file.

  • Wrap constants in a Lambda layer and force them into the model.

  • toy_with_constant.onnx.zip

  • Convert test

    onnx2tf -i toy_with_constant.onnx -nuo -cotof

    ONNX	TFLite

    

  • Inference test

    import tensorflow as tf
    import numpy as np
    from pprint import pprint
    
    interpreter = tf.lite.Interpreter(model_path="saved_model/toy_with_constant_float32.tflite")
    interpreter.allocate_tensors()
    
    input_details = interpreter.get_input_details()
    output_details = interpreter.get_output_details()
    
    interpreter.set_tensor(
        tensor_index=input_details[0]['index'],
        value=np.ones(tuple(input_details[0]['shape']), dtype=np.float32)
    )
    interpreter.invoke()
    
    variable_output = interpreter.get_tensor(output_details[0]['index'])
    constant_output = interpreter.get_tensor(output_details[1]['index'])
    
    print("=================")
    print("Variable Output:")
    pprint(variable_output)
    print("=================")
    print("Constant Output:")
    pprint(constant_output)

    =================
    Variable Output:
    array([[-0.02787317, -0.05505124,  0.05421712,  0.03526559, -0.14131774,
             0.0019211 ,  0.08399964,  0.00433664, -0.00984338, -0.03370604]],
          dtype=float32)
    =================
    Constant Output:
    array([1., 2., 3., 4., 5.], dtype=float32)
    

2. Summary of corrections

3. Before/After (If there is an operating log that can be used as a reference)

4. Issue number (only if there is a related issue)

• Constant outputs removed from ONNX during conversion #627