Hi, I trained a resnet18_v1 on FashionMNIST
when I submit an inference request on one item of the test dataset, the result is a 1000-value array. It should be ten right? since FashionMNIST has 10 categories…
Can someone tell me what is wrong?
inference code is this:
def transform(data, label):
return nd.transpose(data.astype(np.float32), (2,0,1))/255, label.astype(np.float32)
testset = gluon.data.vision.FashionMNIST(train=False, transform=transform)
net(testset[0][0].expand_dims(0).as_in_context(ctx)) # this is shape (1,1000). Why?