Dear pennylane team, I build a hybird classical quantum network using qml.qnn.KerasLayer. But the summary shows that the paramter in the quantum circuit are not used. Here is my code: dev = qml.device("default.qubit", wires=n_qubits) # dev = qml.device("lightning.qubit", wires=n_qubits) # dev = qml…

Hey @AHHil , When you use Sequential, you can also pass it a list: model = tf.keras.models.Sequential([layer1, layer2, layer3]) See the documentation for more details: tf.keras.Sequential | TensorFlow v2.13.0 Let me know if that helps!

I’m sorry that I didn’t explain clearly my question. I want to reserve model = keras.Model(inputs=input, outputs=output) because I need the output of each layer. If I use model = tf.keras.models.Sequential() In this way, I can’t get the output of each layer. I need to process these output such a…

I have solved the problem. According to https://discuss.pennylane.ai/t/quantum-neural-networks-quanvolutional-nn/1111/7 and https://discuss.pennylane.ai/t/transfer-learning-with-pretrained-keras-model/1462/10 . I add this code model(X_train[:2]) behind model = keras.Model(inputs=input, outputs=out…

Awesome! Glad you were able to figure it out :slight_smile:

0 paramters are uesd in the quantum circuit

PennyLane Help

isaacdevlugt August 1, 2023, 2:25pm 5

Awesome! Glad you were able to figure it out

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0 paramters are uesd in the quantum circuit

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