TypeError: can‘t convert CUDA tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory fi

迈不过友情╰ 2022-05-08 02:40 193阅读 0赞

运行程序如下：

import numpy as np
    import torch
    from torch import nn
    from torch.autograd import Variable
    import matplotlib.pyplot as plt
    
    
    class LinearRegression(nn.Module):
        def __init__(self):
            super(LinearRegression,self).__init__()
            self.linear = nn.Linear(1,1)
        def forward(self, x):
            out = self.linear(x)
            return out
    x_train = np.array([[3.3],[4.4],[5.5],[6.710],[6.93],[4.168],[9.779],[6.182],[7.59],[2.167],[7.042],[10.791],[5.313],[7.997],[3.1]],dtype=np.float32)
    y_train = np.array([[1.7],[2.76],[2.09],[3.19],[1.694],[1.573],[3.366],[2.596],[2.53],[1.221],[2.827],[3.465],[1.65],[2.904],[1.3]],dtype=np.float32)
    x_train = torch.from_numpy(x_train)
    y_train = torch.from_numpy(y_train)
    num_epochs = 1000
    if torch.cuda.is_available():
        print("GPU1")
        model = LinearRegression().cuda()
    else:
        print("CPU1")
        model = LinearRegression()
    
    criterion = nn.MSELoss()
    optimizer = torch.optim.SGD(model.parameters(),lr=1e-3)
    
    
    for epoch in  range(num_epochs):
        if torch.cuda.is_available():
            print('GPU2')
            inputs = Variable(x_train).cuda()
            target = Variable(y_train).cuda()
        else:
            print("CPU2")
            inputs = Variable(x_train)
            target = Variable(y_train)
        # forward
        out = model(inputs)
        loss = criterion(out,target)
        # backward
        optimizer.zero_grad()  # 梯度归零
        loss.backward()   # 反向传播
        optimizer.step()  # 更新参数
        # if (epoch+1) % 20 ==0:
        #     print('Epoch[{}/{}], loss:{:,6f}'.format(epoch+1,num_epochs,loss.data[0]))
    
    
    model.eval()
    
    predict = model(Variable(x_train.cuda()))  
    predict = predict.data.numpy()
    plt.plot(x_train.numpy(),y_train.numpy(),'ro',label='Original data')
    plt.plot(x_train.numpy(),predict,label='Fitting Line')
    plt.show()

这行报错：`predict = predict.data.numpy()`

TypeError: can't convert CUDA tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.

意思是:如果想把CUDA tensor格式的数据改成numpy时，需要先将其转换成cpu float-tensor随后再转到numpy格式。 numpy不能读取CUDA tensor 需要将它转化为 CPU tensor  
将`predict.data.numpy()` 改为`predict.data.cpu().numpy()`即可