core.common.tutorial_utils

Functions

fairchem_root()	Return the root directory of the installed fairchem-core package.
fairchem_main()	Return the path to fairchem main.py
describe_fairchem()	Print some system information that could be useful in debugging.
train_test_val_split(ase_db[, ttv, files, seed])	Split an ase db into train, test and validation dbs.
generate_yml_config(checkpoint_path[, yml, delete, update])	Generate a yml config file from an existing checkpoint file.

Module Contents

core.common.tutorial_utils.fairchem_root()

Return the root directory of the installed fairchem-core package.

core.common.tutorial_utils.fairchem_main()

Return the path to fairchem main.py

core.common.tutorial_utils.describe_fairchem()

Print some system information that could be useful in debugging.

core.common.tutorial_utils.train_test_val_split(ase_db, ttv=(0.8, 0.1, 0.1), files=('train.db', 'test.db', 'val.db'), seed=42)

Split an ase db into train, test and validation dbs.

ase_db: path to an ase db containing all the data. ttv: a tuple containing the fraction of train, test and val data. This will be normalized. files: a tuple of filenames to write the splits into. An exception is raised if these exist.

You should delete them first.

seed: an integer for the random number generator seed

Returns the absolute path to files.

core.common.tutorial_utils.generate_yml_config(checkpoint_path, yml='run.yml', delete=(), update=())

Generate a yml config file from an existing checkpoint file.

checkpoint_path: string to path of an existing checkpoint yml: name of file to write to. pop: list of keys to remove from the config update: dictionary of key:values to update

Use a dot notation in update.

Returns an absolute path to the generated yml file.