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TestPowerGradientShiftZero, TestPowerGradient fail with certain boost #1252
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This failed for me with the native BLAS provided by OSX 10.9, so I tried with openBLAS and it gave me the same 3 errors. Does anyone have any suggestions for getting openBLAS to work? |
I built caffe with MKL and also encountered such failures. To be specific, there were actually six failed tests. The boost library used is of the newest version, i.e. 1.57.0, and the Anaconda Python 2.7.
Do the failures indicate that caffe will not work appropriately? How should I deal with them? |
I also just tried compiling with MKL for all my libraries and I am still getting the errors in TestPowerGradient. @II-Matto , you have 6 errors and I have 3 because you are using GPU compilation and I am not. |
I got it to work with MKL and Boost 1.55. |
I've faced same problem and I've solved it. |
Still having the same errors with Boost 1.57, downgrading to 1.55 solved the problem. |
I think the BLAS issue here is a red herring; the tests passed for me with Atlas and Boost 1.55. Boost 1.56 failed with both OpenBLAS and Atlas. |
Agreed, a boost problem then
|
I'm getting it with boost1.54.0. Ubuntu 14.04, boost1.54.0, mkl from intel version 15 c++. |
Confirm the same problem here. CentOS6, boost 1.57, mkl-203
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@shelhamer, as users, should we be concerned about the test failures with Boost 1.57? Will Caffe give erroneous results? Or can we ignore the failures for now? |
Same problem(6 failed test) at first, on OSX 10.9.5 with atlas, boost 1.57 and Anaconda Python 2.7. After downgrading boost to 1.55(others remain unchanged) and reinstall caffe, it works now |
While I can't dismiss these numerical errors, the consolation is that these are isolated to |
The gradient checker fails on certain elements of the PowerLayer checks, but only 1-3 sometimes fail out of the 120 elements tested. This is not due to any numerical issue in the PowerLayer, but the distribution of the random inputs for the checks. boost 1.56 switched the normal distribution RNG engine from Box-Muller to Ziggurat.
I looked into this a little and @jeffdonahue was quick to note that boost RNG is used by all the fillers regardless of mode -- and I found this boost thread on RNG that notes the normal distribution RNG was rewritten for the 1.56 release. A little good old fashioned hand calculation confirmed this is nothing more than a precision error, so #1840 fixes this by reducing the step size for the finite-differencing. There's no need to keep to boost 1.55. (For those who like RNG the switch was from Box-Muller to Ziggurat.) |
The gradient checker fails on certain elements of the PowerLayer checks, but only 1-3 sometimes fail out of the 120 elements tested. This is not due to any numerical issue in the PowerLayer, but the distribution of the random inputs for the checks. boost 1.56 switched the normal distribution RNG engine from Box-Muller to Ziggurat.
The gradient checker fails on certain elements of the PowerLayer checks, but only 1-3 sometimes fail out of the 120 elements tested. This is not due to any numerical issue in the PowerLayer, but the distribution of the random inputs for the checks. boost 1.56 switched the normal distribution RNG engine from Box-Muller to Ziggurat.
The
PowerLayer::Backward
checks seem to fail with certain versions of boost on OS X / ubuntu.boost 1.55 passes, but boost 1.56 and and 1.57 fail.
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