batch_size,shuffle=True)forX,yindata_iter:print(X,y)break# model define and initmodel=LinearNet(num_inputs)dp_model=torch.nn.DataParallel(model)dp_model.cuda()print(dp_model)# cost functionloss=nn.MSELoss()# optimizeroptimizer=torch.optim.SGD(dp_model.parameters(),lr=0.03)# trainnum_epo...