CNN_spectroscopy

1. Edits to the PyTorch code and Future edits : Kunal Ghosh
2. original Author of PyTorch code : Mathias Smeds
3. based on code in Theano by : Kunal Ghosh

Packages

1. conda install pytorch torchvision cudatoolkit=9.0 -c pytorch
2. conda install scikit-learn

Running instructions

stdbuf -oL -eL python3 spectroscopy_run_experiments.py ../../data/132k_16_opt_eV/spectra.npz ../../data/132k_16_opt_eV/coulomb.npz 1000 exp00 rmse 300 0.1 |& tee -a 0_1_output.txt

• stdbuf -oL -eL ensures that python uses linebuffering for output and error streams respectively.
• In addition to the the stdbuf one must flush the stdout and stderr in the training loop.
• By default 0.05 percent of total data (6627 datapoints) is used for test and validation sets.
• The last positional argument 0.1 in the example above indicates the percent of the total data (excluding test and validation set) that is used for training.
• |& pipes both the stdout and stderr.
• tee -a appends everything that is piped to the text file (here 0_1_output.txt) and also prints it out to stdout.