5.4. [train] section

abics_train creates and trains a regression model from configurations to energies. Indeed, abics_train uses an external program to train the model. In the current version, only aenet is supported as an external program. For software-specific notes (such as input file names), see Machine learning trainer/calculator-specific notes.

The input information for abics_train is described in the [trainer] section. The description of each parameter is as follows. An example is shown as follows:

[trainer] # Configure the model trainer.
type = 'aenet'
base_input_dir = '. /aenet_train_input'
exe_command = ['~/git/aenet/bin/generate.x-2.0.4-ifort_serial',
             'srun ~/git/aenet/bin/train.x-2.0.4-ifort_intelmpi']
ignore_species = ["O"]

5.4.1. Input Format

Keywords and their values are specified by a keyword and its value in the form keyword = value. Comments can also be entered by adding # (Subsequent characters are ignored).

5.4.2. Key words

• type

  Format : str

  Description : The trainer to generate the neural network potential (currently only ‘aenet’).

• base_input_dir

  Format : str

  Description : Path of the directory containing the input files that the learner refers to.

• exe_command

  Format : list of str

  Description : List of commands to execute; if you use aenet, you need to specify the path to generate.x and train.x.

• ignore_species

  Format : list

  Description : Same as ignore_species in [sampling.solver] section. Specify atomic species to “ignore” in neural network models such as aenet. For those that always have an occupancy of 1, it is computationally more efficient to ignore their presence when training and evaluating neural network models.