def predict_tf_lite(model, image):
    """
    TFLite model prediction (forward propagate)
    :param model: TFLite interpreter
    :param image: Input image
    :return: Numpy array with logits
    """
    input_details = model.get_input_details()
    output_details = model.get_output_details()
    model.set_tensor(input_details[0]['index'], image)
    model.invoke()
    # n_outputs = len(output_details)
    outputs = []
    # import ipdb; ipdb.set_trace()
    for i in range(len(output_details)):
        tf_lite_output = model.get_tensor(output_details[i]['index'])
        outputs += [tf_lite_output]
    outputs = sorted(outputs, key=lambda x: x.shape)
    return outputs