kliff.transforms.configuration_transforms.graphs

class kliff.transforms.configuration_transforms.graphs.RadialGraph(species, cutoff, n_layers=1, copy_to_config=False, mic=False)[source]

Generate a graph representation of a configuration. This generator will also save the required parameters for porting the model over to KIM-API using TorchMLModelDriver. The configuration file saved here will generate identical graphs at KIM-API runtime. For porting the graph representation you also need to provide the TorchScript model file name.

Parameters:

  • species (list) – List of species.

  • cutoff (float) – Cutoff distance.

  • n_layers (int) – Number of convolution layers.

  • copy_to_config (bool) – If True, the graph will be copied to the Configuration object’s fingerprint attribute.

  • mic (bool) – If True, module will return conventional MIC graphs, as opposed to the parallel staged graphs.

forward(configuration)[source]

Generate a graph representation of a configuration.

Parameters:

configuration (Configuration) – Instance of ~:class:kliff.dataset.Configuration. For which the graph representation is to be generated.

Return type:

PyGGraph

Returns:

C++ custom graph object or Pytorch Geometric Data object.

static to_py_graph(graph)[source]

Convert a C++ graph object to a KLIFF Geometric Graph Data object, GraphData.

Parameters:

graph (GraphData) – C++ graph data object.

Return type:

PyGGraph

Returns:

PyGGraph object.

export_kim_model(path, model)[source]

Save the transform toa text file for reuse. This is currently used to load the model into KIM-API for pre-processing. The model name is also required to correctly load the model into KIM-API.

Parameters:

  • path (Path) – Path to save the parameter file.

  • model (str) – name of model to save.

class kliff.transforms.configuration_transforms.graphs.PyGGraph(*args: Any, **kwargs: Any)[source]

A Pytorch Geometric compatible graph representation of a configuration. When loaded into a class:torch_geometric.data.DataLoader the graphs of type PyGGraph will be automatically collated and batched.

classmethod from_dict(mapping)[source]

Create a PyGGraph object from a dictionary.

Parameters:

mapping (Dict[str, Any]) – Dictionary containing the graph data.

Returns:

PyGGraph object.

to_dict()[source]

Convert the PyGGraph object to a dictionary.

Returns:

Dictionary containing the graph data.