noise = torch.FloatTensor(np.random.normal(0,0.02,(len(batch['img128']), 64))).to(device)

This line of code generates a tensor of random noise with dimensions (batch_size, 64) using NumPy's normal distribution function. The mean of the distribution is set to zero and the standard deviation is set to 0.02. The tensor is then converted to a PyTorch FloatTensor and moved to the device specified by the 'device' variable. This random noise tensor can be used as an input to a generator network in a generative adversarial network (GAN) to generate new images.