5.5. [train] section¶
We create neural network potentials by learning the results of ab initio calculations made by abics_train using aenet.
The input information for abics_train is described in the [trainer]
section. The description of each parameter is as follows.
This section specifies the type of physical quantity to be acquired. 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"]
5.5.1. 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).
5.5.2. 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
andtrain.x
.ignore_species
Format : list
Description : Same as
ignore_species
in [sampling.solver] section. Specify atomic species to “ignore” in neural network models such asaenet
. 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.