Question

我正在使用共享的here代码来测试CNN图像分类器。调用测试函数时，我在line 155上收到了此错误：

test_acc += torch.sum(prediction == labels.data)
TypeError: eq() received an invalid combination of arguments - got (numpy.ndarray), but expected one of:
 * (Tensor other)
      didn't match because some of the arguments have invalid types: ([31;1mnumpy.ndarray[0m)
 * (Number other)
      didn't match because some of the arguments have invalid types: ([31;1mnumpy.ndarray[0m)

test函数的片段：

def test():
    model.eval()
    test_acc = 0.0
    for i, (images, labels) in enumerate(test_loader):

        if cuda_avail:
                images = Variable(images.cuda())
                labels = Variable(labels.cuda())

        #Predict classes using images from the test set
        outputs = model(images)
        _,prediction = torch.max(outputs.data, 1)
        prediction = prediction.cpu().numpy()
        test_acc += torch.sum(prediction == labels.data) #line 155



    #Compute the average acc and loss over all 10000 test images
    test_acc = test_acc / 10000

return test_acc

快速搜索后，我发现该错误可能与SO question中的prediction和labels之间的比较有关。

如何解决此问题，而不对其余代码进行打扰？

Answer 1

您为什么在<input type='file' webkitdirectory='' directory='' multiple='true' />有.numpy()？这样，您可以将PyTorch张量转换为NumPy数组，从而使其类型与prediction = prediction.cpu().numpy()不兼容。

删除labels.data部分应该可以解决此问题。

无效的参数组合-eq（）

1 个答案: