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< davida>
zoq: Done. Uploaded to the data directory on my GitHub. Note that the trainSetX.bin is in a compressed file as it was too large for a GitHub upload.
< davida>
zoq: Note that the data is saved raw, i.e. pre-normalisation.
< zoq>
davida: Thanks!
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< zoq>
davida: which is I think is close to the tf result.
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< davida>
zoq: I got disconnected for a while so just catching up with your message in the mlpack irc log. Can you tell me how you set the MaxIterations when you set the BatchSize = 1 ?
< davida>
Could you also share any other changes you might have made?
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< davida>
zoq: the reason I ask is that setting the batchsize to 1 and leaving MaxIter=10000 seems to take forever to run on my PC. I have had it running for about 20mins and have not even had 5 Epochs complete.
< davida>
zoq: First 5 Epochs result for me with BatchSize=1 and MaxItr=1080:
< davida>
Epoch: 0 Training Accuracy = 16.6667% Test Accuracy = 16.6667%
< davida>
Epoch: 5 Training Accuracy = 16.6667% Test Accuracy = 16.6667%
< davida>
... so all you did was change the 64 -> 1 ?
< zoq>
I think so, I used Week1Main.cpp and not the latest ConvolutionModelApplication.cpp.
< davida>
I made changes to that since I uploaded it. Could you please paste the optimizer line for me.
< davida>
OK - figured out how to get the deleted file back from GitHub. I see that was set to BatchSize=1 and MaxIters=1080. I tried that on my computer and it failed to get better than 16% for 100 epochs. It looks like I may have a problem
< davida>
in my libraries.
< davida>
I am first trying with CUDA NVBLAS turned off to see it that is affecting it at all.
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< davida>
zoq: ok - I disabled CUDA NVBLAS and it didn't change anything on my end in terms of results, although it did slow it down a lot.
< zoq>
davida: Okay, turns out, I haven't changed the batch size, strange, did you build mlpack with -DDEBUG=ON?
< davida>
I think I did.
< davida>
zoq: yes - I am using debug versions of both Armadillo and MLPACK
< davida>
zoq: will that cause me a problem? I can switch to the 'release' versions of the libraries
< davida>
zoq: .... but not sure why that would impact anything other than slowing it down.
< zoq>
It shouldn't change anything right, I will rerun the example on another system as well.
< davida>
zoq: I realised I did not actually compile the RELEASE version of MLPACK. However, as I am compiling a release version I am getting a few errors. The first is "Unknown binding type". It is coming from mlpack_main.hpp which seems should only be included in command line versions.
< davida>
zoq: I am also getting a lot of DLLIMPORT errors.
< davida>
zoq: Is there a compile switch for BINDING_TYPE that needs to be set for building the libraries?
< zoq>
davida: If you don't need the pythoin bindings, I would jsut set -DBUILD_PYTHON_BINDINGS=OFF
< zoq>
davida: Also, with latest version do you mean the master branch?
< davida>
I built 3.0.3 a while ago. That is what I have on my computer
< zoq>
davida: Do you mind to test against the master brnach?
< davida>
See also "D:/sdk/mlpack/mlpack/build/CMakeFiles/CMakeOutput.log".
< davida>
strange.
< zoq>
davida: Did you build with -DBUILD_PYTHON_BINDINGS=OFF?
< davida>
I will try to build anyway.
< davida>
I am running CMAKE right now.
< davida>
zoq: In tha make it says this:
< davida>
CMake Warning at CMakeLists.txt:31 (message):
< davida>
By default Python bindings are not compiled for Windows because they are
< davida>
not known to work. Set BUILD_PYTHON_BINDINGS to ON if you want them built.
< davida>
zoq: I think this means they are off
< rcurtin>
davida: if Python bindings are off, there shouldn't be any error "Could NOT find PythonInterp"---that part of the code shouldn't even be getting called
< zoq>
maybe we missed something
< rcurtin>
davida: you might need to remove CMakeCache.txt or something like this and try reconfiguring
< rcurtin>
I will say, I am a little confused to see that error; I can't reproduce anything like it on Linux
< davida>
zoq: rcurtin: I added the -DBUILD_PYTHON_BINDINGS=OFF to the cmake line and it worked this time.