How to use HDNNP¶
Data generation¶
Pre-processing¶
OUTCAR
to .xyz format file,
but in the same way you can convert the output of other DFT calculation program to .xyz format file.Training¶
Configuration¶
A default configuration file for training is located in examples/training_config.py
.
training_config.py
consists of some subclasses that inherits traitlets.config.Configurable
:
- c.Application.xxx
- c.TrainingApplication.xxx
- c.DatasetConfig.xxx
- c.ModelConfig.xxx
- c.TrainingConfig.xxx
Following configurations are required, and remaining configurations are optional.
- c.DatasetConfig.parameters
- c.ModelConfig.layers
- c.TrainingConfig.data_file
- c.TrainingConfig.batch_size
- c.TrainingConfig.epoch
- c.TrainingConfig.order
- c.TrainingConfig.loss_function
- c.TrainingConfig.interval
- c.TrainingConfig.patients
For details of each setting, see training_config.py
Command line interface¶
Execute the following command in the directory where training_config.py
is located.
$ hdnnpy train
Note
c.TrainingConfig.out_dir
already exists, it overwrites the existing file in the directory.c.TrainingConfig.out_dir
for each execution.Prediction¶
Configuration¶
A default configuration file for prediction is located in examples/prediction_config.py
.
prediction_config.py
consists of some subclasses that inherits traitlets.config.Configurable
:
- c.Application.xxx
- c.PredictionApplication.xxx
- c.PredictionConfig.xxx
Following configurations are required, and remaining configurations are optional.
- c.PredictionConfig.data_file
- c.PredictionConfig.order
For details of each setting, see prediction_config.py
Command line interface¶
Execute the following command in the directory where prediction_config.py
is located.
$ hdnnpy predict
Post-processing¶
HDNNP-LAMMPS interface program
Command line interface¶
Execute the following command.
$ hdnnpy convert
$ hdnnpy convert -h