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