This would just be a small quality-of-life improvement. Currently, deepsignal.py imports train_model and call_mods even when I am actually calling extract. train_model and call_mods then want to import tensorflow, and tensorflow depends on libcuda, none of which is required by the feature extraction command.
This can be a bit problematic in a compute cluster environment where you have dedicated GPU nodes (which have libcuda) and non-GPU nodes (which don't have libcuda). It forces me to run the feature extraction on a GPU node, despite it not using a GPU, thus reserving a valuable resource I'm not actually using.
PengNi
commented
4 years ago
Hi!
This would just be a small quality-of-life improvement. Currently, deepsignal.py imports train_model and call_mods even when I am actually calling extract. train_model and call_mods then want to import tensorflow, and tensorflow depends on libcuda, none of which is required by the feature extraction command.
This can be a bit problematic in a compute cluster environment where you have dedicated GPU nodes (which have libcuda) and non-GPU nodes (which don't have libcuda). It forces me to run the feature extraction on a GPU node, despite it not using a GPU, thus reserving a valuable resource I'm not actually using.
Thanks a lot!