run:

$ bash bin/run_train.sh

to run a sample training. Resulting images are created into images/

for interactive example of using SRBM and setting hyperparameters, see notebook/SRBM_unsup_gen.

Before uploading to git, run:

$ bash bin/run_check.sh

To run pytest and test notebook.

Or for automated push, run:

$ bash bin/git_push.sh

For conda users, use:

$ conda env create -f environment.yml -n qftml

or for pip users,

$ python -m pip install -r requirements.txt

to setup the environment

• Source code is in RBM/
• New features under dev is in RBM/test/
• Once the code under RBM/test/ is tested and implemented, the old code is transferred to RBM.old/