e7fa0a6bac
- update lammps python package to use setuptools - refactor MLIAP classes into lammps python package lammps.mliap package - change TorchWrapper to use dtype and device as arguments - turn activation of mliappy into functions (was a class) - add a check to see if python interpreter is compatible with python lib calls internal to lammps mliap_model_python_couple.pyx: - load models ending in '.pt' or '.pth' with pytorch rather than pickle
27 lines
874 B
Python
27 lines
874 B
Python
import sys
|
|
import numpy as np
|
|
import torch
|
|
|
|
# torch.nn.modules useful for defining a MLIAPPY model.
|
|
from lammps.mliap.pytorch import TorchWrapper, IgnoreElems
|
|
|
|
# Read coefficients
|
|
coeffs = np.genfromtxt("Ta06A.mliap.model",skip_header=6)
|
|
|
|
# Write coefficients to a pytorch linear model
|
|
bias = coeffs[0]
|
|
weights = coeffs[1:]
|
|
lin = torch.nn.Linear(weights.shape[0],1)
|
|
lin.to(torch.float64)
|
|
with torch.autograd.no_grad():
|
|
lin.weight.set_(torch.from_numpy(weights).unsqueeze(0))
|
|
lin.bias.set_(torch.as_tensor(bias,dtype=torch.float64).unsqueeze(0))
|
|
|
|
# Wrap the pytorch model for usage with mliappy coupling.
|
|
model = IgnoreElems(lin) # The linear module does not use the types.
|
|
n_descriptors = lin.weight.shape[1]
|
|
n_elements = 1
|
|
linked_model = TorchWrapper(model,n_descriptors=n_descriptors,n_elements=n_elements)
|
|
|
|
torch.save(linked_model,"Ta06A.mliap.pytorch.model.pt")
|