I’m trying to use sample weights for the NLLLoss (similar to Keras’s weight argument). I thought I could do:
loss_function = nn.NLLLoss(reduce=False)
But I’m getting the error:
TypeError: init() got an unexpected keyword argument ‘reduce’
I was assuming this is because my pytorch version (torch 0.2.0.post4) didn’t have this option incorporated yet.
So I tried installing installing from master, but I’m getting the error:
CMake Error at CMakeLists.txt:1 (cmake_minimum_required): CMake 3.0 or higher is required. You are running version 22.214.171.124 -- Configuring incomplete, errors occurred! ---------------------------------------- Rolling back uninstall of torch Command "/home/nhartman/miniconda3/envs/rafaelEnv/bin/python -u -c "import setuptools, tokenize;__file__='/tmp/pip-xl7r5mzy-build/setup.py';f=getattr(tokenize, 'open', open)(__file__);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, __file__, 'exec'))" install --record /tmp/pip-ewkrv8v7-record/install-record.txt --single-version-externally-managed --compile" failed with error code 1 in /tmp/pip-xl7r5mzy-build/
My questions are:
(1) Do I actually need to reinstall pytorch from the source, or am I just not understanding how the NLLLoss() function works?
(2) If I need to install the new version for this functionality, can I do so without upgrading make (b/c I don’t have “sudo” privileges on this machine).
Thanks in advance!