Pennylane-Lightning GPU

PennyLane Plugins PennyLane Lightning
9

Hi @George_LA and @mlxd and @isaacdevlugt,

Even I tried the solution given by @mlxd, however, I was not able to run the script.

So, instead, I did this:

import torch
device = torch.device("cuda:0" if (torch.cuda.is_available()) else "cpu")

I created the quantum circuit under a class. Then, I sent it to the GPU. It was able to utilize it.

class QCNN(nn.Module):

    def CONVCircuit(phi, wires, i=0):

    """
    quantum convolution Node
    """
    # parameter
         theta = np.pi / 2

         qml.RX(phi[0] * np.pi, wires=0)
         qml.RX(phi[1] * np.pi, wires=1)
         qml.RX(phi[2] * np.pi, wires=2)
         qml.RX(phi[3] * np.pi, wires=3)

         qml.CRZ(theta, wires=[1, 0])
         qml.CRZ(theta, wires=[3, 2])
         qml.CRX(theta, wires=[1, 0])
         qml.CRX(theta, wires=[3, 2])
         qml.CRZ(theta, wires=[2, 0])
         qml.CRX(theta, wires=[2, 0])

    # Expectation value
          measurement = qml.expval(qml.PauliZ(wires=0))

          return measurement


     def QCONV1(X, image_number, image_total, step=2):
    """
    quantum convolutional layer
    """

    #H, W, CH = X.shape
          H, W = X.shape
          step2 = 2
          out = np.zeros(((H//step), (W//step)))
    #progress = 0
          for i in range(0, W, step):
        #print("processing image "+str(image_number)+"/ "+str(image_total)+": "+str(int(((i/W+1))*100))+"% ", end="\r")
               print("processing image "+str(image_number)+"/ "+str(image_total)+": "+str(i)+"px   ", end="\r")
               for j in range(0, H, step):
            # get 2x2 pixels and make them 1D array
                     phi = X[i:i+2, j:j+2].flatten()
            # Get Measurement
                     measurement = CONVCircuit(phi, len(phi))
                     out[i//step, j//step] = measurement

           return out

qcnn = QCNN().to(device)
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