Untitled
unknown
python
a year ago
660 B
4
Indexable
model.load_state_dict(torch.load("mnist_cnn.pt")) weight1 = model.conv1.weight.int().tolist() weight2 = model.conv2.weight.int().tolist() @fhe.compiler({"x": "encrypted"}) def f(x): x = fhe.conv(x, weight1, kernel_shape=(3, 3), strides=(1, 1)) x = fhe.relu(x) x = fhe.conv(x, weight2, kernel_shape=(3, 3), strides=(1, 1)) x = fhe.relu(x) return x inputset = [np.random.randint(0, 255, size=(1, 1, 28, 28)) for _ in range(10)] circuit = f.compile(inputset, relu_on_bits_threshold=9, use_gpu=True) sample = np.random.randint(0, 255, size=(1, 1, 28, 28)) assert np.array_equal(circuit.encrypt_run_decrypt(sample), f(sample))
Editor is loading...
Leave a Comment