deepmd.tf.modifier.base_modifier

deepmd.tf.modifier.base_modifier#

Classes#

BaseModifier

Potential energy model.

Module Contents#

class deepmd.tf.modifier.base_modifier.BaseModifier(*args, **kwargs)[source]#

Bases: deepmd.tf.infer.DeepPot, make_base_modifier()

Potential energy model.

Parameters:
model_filePath

The name of the frozen model file.

*argslist

Positional arguments.

auto_batch_sizebool or int or AutoBatchSize, default: True

If True, automatic batch size will be used. If int, it will be used as the initial batch size.

neighbor_listase.neighborlist.NewPrimitiveNeighborList, optional

The ASE neighbor list class to produce the neighbor list. If None, the neighbor list will be built natively in the model.

**kwargsdict

Keyword arguments.

Examples

>>> from deepmd.infer import DeepPot
>>> import numpy as np
>>> dp = DeepPot("graph.pb")
>>> coord = np.array([[1, 0, 0], [0, 0, 1.5], [1, 0, 3]]).reshape([1, -1])
>>> cell = np.diag(10 * np.ones(3)).reshape([1, -1])
>>> atype = [1, 0, 1]
>>> e, f, v = dp.eval(coord, cell, atype)

where e, f and v are predicted energy, force and virial of the system, respectively.