118 :param b: Divisor
119 :return: Quotient of the two polynomials
120 """
121 q, r = qr(a.c, b.c)122 return np.poly1d(q)
123
124def main():
16
17 def test_measure_state(self):
18 qai = QuantumAI(4)
19 result = qai.measure_state()20 # Assert that the measurement is correct
21
22if __name__ == "__main__":
5 def test_execute_circuit(self):
6 qi = QiskitIntegration('qasm_simulator')
7 circuit = QuantumCircuit(4)
8 result = qi.execute_circuit(circuit) 9 # Assert that the circuit is executed correctly
10
11if __name__ == "__main__":
21 # Implement a method to get the embedding of the multi-modal data
22 # For example, using a pre-trained model like CLIP
23 from clip import clip
24 model, preprocess = clip.load("ViT-B/32", device="cuda")25 image_embedding = model.encode_image(self.get_image().unsqueeze(0))
26 text_embedding = model.encode_text(self.get_text())
27 return torch.cat((image_embedding, text_embedding), dim=1)
35 tf.contrib.util.make_tensor_proto(self.model.input_data))
36
37 # Receive response
38 result = stub.Predict(request, 10.0) # 10 secs timeout39
40 # Close the channel when done
41 channel.close()
An unused variable takes up space in the code, and can lead to confusion, and it should be removed. If this variable is necessary, name the variable _
to indicate that it will be unused, or start the name with unused
or _unused
.
def update():
for i in range(10): # Usused variable `i`
time.sleep(0.01)
display_result()
def update():
for _ in range(10):
time.sleep(0.01)
display_result()