Andrew Kern

I've tried to fix this over in #3235

an example pool file can be found here: https://github.com/kr-colab/ReLERNN/blob/master/examples/example.pool there are three columns: the chrom name, the position on the chrom, and the allele frequency in the pool. you need...

can you give some more details about the conda environment? the output of `conda list` should be a good start

So looking over things it looks like the correct libs are being installed, but given that you are getting warnings like: ``` W tensorflow/core/common_runtime/gpu/gpu_device.cc:1960] Cannot dlopen some GPU libraries. Please...

by the way this has nothing to do with `ReLERNN` per se-- this is about how your HPC is managing their nvidia setup. You might just reach out to them...

this looks like it is running on your GPU @OliverPStuart. Can you confirm that the GPU is seeing load? A good tool for this is `nvitop` as for the `ulimit`...

hmmm... you are still having issues that are related to your compute setup. i'm guessing there are duplicate versions of tensorflow/cuda throughout the system. First please run this and report...

okay you've got a mixed environment issue. the key here is to unset your LD_LIBRARY_PATH or specify it explicitly. if you run the following, does it relieve the “factory already...

hmm... out of interest are you running this on a cluster? did you just run that test on a head node that doesn't have GPUs exposed?

hi there-- to help debug this can you give me a full list of the versions in your python environment? assuming you use `conda` you can get this with `conda...