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dmlc / mshadow

Matrix Shadow:Lightweight CPU/GPU Matrix and Tensor Template Library in C++/CUDA for (Deep) Machine Learning
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<gpu> and <cpu> generates totally different results #50

Open DrustZ opened 9 years ago

DrustZ commented 9 years ago

Help. I improved the /guide/neuralnet/convnet.cu, add my own function when I use -cpu parameter, things go well , the error rate is declining however, -gpu generates totally different results: the error just stays at 0.9 or so(didn't change a little bit)... It may seems there's a bug in mshadow's gpu implementation, but I don't know.

I didn't add my own gpu code, just use mshadow's(like <xpu>).

for cpu , I used blas lib. And my cuda version is 7.0. Please help. @tqchen @antinucleon

DrustZ commented 9 years ago

besides, when I change the configuration of stride, ksize and pad, the outputs are also not the same. some configuration work well on both cpu and gpu, but some only on cpu.

DrustZ commented 9 years ago

Is there any probability that GPU and CPU performs differently on = and Copy? I use a lot of = between tensor and expression, following the original convent version. And I also use Copy, which is used when = can't work (like tensor[i] = tensor2.Slice(a, a+1) or tensor[i] = tensor2[i] What's more, I used expression like tensor.Slice(i, i+1) = some expression, is this valid? or do I must turn it into Copy(tensor.Slice(i, i+1) , exp, stream_)?

Please help. @tqchen @antinucleon

DrustZ commented 9 years ago

I set all tensor's stream, and in GPU mode it didn't report error. Is there a bug or other reason that GPU and CPU performs differently?

DrustZ commented 9 years ago

Besides, I used a std::vector to store tensors, like vector[i] = tensor

DrustZ commented 9 years ago

I'll be really really grateful if someone has some idea to help me.

antinucleon commented 9 years ago

Could post you code with gist so I can have a glance?

tqchen commented 9 years ago

Note there is a special semantics on = in mshadow. So when you assign a tensor to another, it is a pointer copy instead of a assignment. So if you intended it be be an assignment, use

Copy(dst, src);

Or

dst = F<op::identity>(src);

Or

dst =1.0f * src;
szha commented 5 years ago

This code base has been donated to the Apache MXNet project per #373, and repo is deprecated. Future development and issue tracking should continue in Apache MXNet.