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Use jax functions

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This commit is contained in:
rohskopf
2023-05-24 13:08:10 -06:00
parent d66504be81
commit b2e5f93d49
1 changed files with 4 additions and 3 deletions
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5
examples/mliap/jax/mliap_unified_jax.py
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@ -17,6 +17,7 @@ class MLIAPUnifiedJAX(MLIAPUnified):
# pair_coeff * * 1 1
self.epsilon = epsilon
self.sigma = sigma
# TODO: Take this from the LAMMPS Cython side.
self.npair_max = 250000
def compute_gradients(self, data):
@ -48,7 +49,7 @@ class MLIAPUnifiedJAX(MLIAPUnified):
@partial(jax.jit, static_argnums=(0,))
def compute_pair_ef(self, rij):
r2inv = 1.0 / np.sum(rij ** 2, axis=1)
r2inv = 1.0 / jnp.sum(rij ** 2, axis=1)
r6inv = r2inv * r2inv * r2inv
lj1 = 4.0 * self.epsilon * self.sigma**12
@ -56,5 +57,5 @@ class MLIAPUnifiedJAX(MLIAPUnified):
eij = r6inv * (lj1 * r6inv - lj2)
fij = r6inv * (3.0 * lj2 - 6.0 * lj2 * r6inv) * r2inv
fij = fij[:, np.newaxis] * rij
fij = fij[:, jnp.newaxis] * rij
return eij, fij