code: def model(get_circuit, n_qubits, output_dim):
      """Fixture for creating a hybrid Keras model. The model is composed of KerasLayers sandwiched
      between Dense layers."""
      c, w = get_circuit
      layer1 = KerasLayer(c, w, output_dim)
      layer2 = KerasLayer(c, w, output_dim)
  
      m = tf.keras.models.Sequential(
          [
              tf.keras.layers.Dense(n_qubits, input_shape=(n_qubits,)),
              layer1,
              tf.keras.layers.Dense(n_qubits),
              layer2,
              tf.keras.layers.Dense(output_dim),
          ]
      )
  
      return m
  
imports: from collections import defaultdict
  import numpy
  import pytest
  import pennylane
label_desc: Use image node_id 1 for calling a global function with example usage: model(get_circuit, n_qubits, output_dim) and returns: m