I’m just start coding with Tensorflow-Quantum (TFQ), it’s a really nice module. In the tutorial I found one can setup a Variational Quantum Circuit (VQC) by something like
# Build the Keras model.
model = tf.keras.Sequential([
    # The input is the data-circuit, encoded as a tf.string
    tf.keras.layers.Input(shape=(), dtype=tf.string),
    # The PQC layer returns the expected value of the readout gate, range [-1,1].
    tfq.layers.PQC(model_circuit, model_readout),
])

The PQC Layer seems to need to specify the operators(model_readout). The process of the tutorial circuit is

Data Encode → Parametrized Gates → Measurement

I want to build a quantum circuit with the process looks like

Data Encode → Parametrized Gates → Data Encode → Parametrized Gates → .etc → Measurement

which is a technique called “Data-Reuploading” by Adrián Pérez Salinas 1
However, the PQC Layers seems couldn’t do the way I want because it need to specified with operators. Is there any way to create a Parametrized Layer only without any operators(measurement). Thank you so much.