Three variants of QCNN, i.e., QCNNCOMPLEX, QCNNREAL, and QCNNRY are implemented.

Author: Chee Kwan Gan

tests/test_models_qcnn.py

@@ -1,14 +1,14 @@
 import pytest
 
-pytest.skip("Soon to be moved to `qiboml`.", allow_module_level=True)
+# pytest.skip("Soon to be moved to `qiboml`.", allow_module_level=True)
 
 import math
 
 import numpy as np
 
 from qibo import gates, set_backend
 from qibo.models import Circuit
-from qibo.models.qcnn import QuantumCNN
+from qiboml.models.qcnn import QuantumCNN
 
 num_angles = 21
 angles0 = [i * math.pi / num_angles for i in range(num_angles)]
@@ -21,7 +21,7 @@ def test_classifier_circuit2():
     nlayers = int(nqubits / 2)
     init_state = np.ones(2**nqubits) / np.sqrt(2**nqubits)  #
 
-    qcnn = QuantumCNN(nqubits, nlayers, nclasses=2)  # , params=angles0)
+    qcnn = QuantumCNN(quantum_model='QCNNCOMPLEX',nqubits=nqubits, nlayers=nlayers, nclasses=2)  # , params=angles0)
 
     angles = [0] + angles0
 
@@ -86,7 +86,7 @@ def test_classifier_circuit4():
     nlayers = int(nqubits / 2)
     init_state = np.ones(2**nqubits) / np.sqrt(2**nqubits)  #
 
-    qcnn = QuantumCNN(nqubits, nlayers, nclasses=2)
+    qcnn = QuantumCNN('QCNNCOMPLEX',nqubits, nlayers, nclasses=2)
     angles = [0] + angles0 + angles0
 
     circuit = qcnn.Classifier_circuit(angles)
@@ -275,7 +275,7 @@ def CNOT_unitary(nqubits, bit0, bit1):
 
 def test_1_qubit_classifier_circuit_error():
     try:
-        QuantumCNN(nqubits=1, nlayers=1, nclasses=2)
+        QuantumCNN('QCNNCOMPLEX',nqubits=1, nlayers=1, nclasses=2)
     except:
         pass
 
@@ -296,7 +296,7 @@ def test_qcnn_training():
     testbias = np.zeros(1)
     testangles = [random.uniform(0, 2 * np.pi) for i in range(21 * 2)]
     init_theta = np.concatenate((testbias, testangles))
-    test_qcnn = QuantumCNN(nqubits=4, nlayers=1, nclasses=2, params=init_theta)
+    test_qcnn = QuantumCNN('QCNNCOMPLEX',nqubits=4, nlayers=1, nclasses=2, params=init_theta)
     testcircuit = test_qcnn._circuit
     result = test_qcnn.minimize(
         init_theta, data=data, labels=labels, nshots=10000, method="Powell"
@@ -318,7 +318,7 @@ def test_two_qubit_ansatz():
     circuit.add(gates.H(0))
     circuit.add(gates.RX(0, 0))
     circuit.add(gates.CNOT(1, 0))
-    test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=circuit)
+    test_qcnn = QuantumCNN(quantum_model='QCNNCOMPLEX',nqubits=4, nlayers=2, nclasses=2, twoqubitansatz=circuit)
 
 
 def test_two_qubit_ansatz_training():
@@ -329,7 +329,7 @@ def test_two_qubit_ansatz_training():
     circuit.add(gates.H(0))
     circuit.add(gates.RX(0, 0))
     circuit.add(gates.CNOT(1, 0))
-    test_qcnn = QuantumCNN(4, 2, 2, twoqubitansatz=circuit)
+    test_qcnn = QuantumCNN(quantum_model='QCNNCOMPLEX',nqubits=4, nlayers=2, nclasses=2, twoqubitansatz=circuit)
 
     data = np.zeros([2, 16])
     for i in range(2):