I got this message in using Keras to train an RNN for language model with a big 3D tensor (generated from a text, one hot encoded, and results a shape of (165717, 25, 7631)):
WARNING (theano.configdefaults): g++ not detected ! Theano will be unable to
execute optimized C-implementations (for both CPU and GPU) and will default to
Python implementations. Performance will be severely degraded. To remove this
warning, set Theano flags cxx to an empty string.
ERROR (theano.sandbox.cuda): nvcc compiler not found on $PATH. Check your nvcc
installation and try again.
But everything goes well while I limit the size of data set into small. Thus I wonder that does Theano or CUDA limit the size of matrix?
Besides, do I have a better way to do one hot representation? I mean, in the large 3D tensor, most elements are 0 due to the one-hot representation. However, I didn't found a layer which accepts index representation of words.
conda install mingw libpython
Make sure this is installed. Get this answer from another post, https://stackoverflow.com/a/31109547/3598832, which indicated from the manual.
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