def comp_ef(self, dcoord, dbox, dtype, tnatoms, name, reuse=None):
descrpt, descrpt_deriv, rij, nlist \
= op_module.prod_env_mat_r(dcoord,
dtype,
tnatoms,
dbox,
tf.constant(self.default_mesh),
self.t_avg,
self.t_std,
rcut = self.rcut,
rcut_smth = self.rcut_smth,
sel = self.sel)
inputs_reshape = tf.reshape(descrpt, [-1, self.ndescrpt])
atom_ener = self._net(inputs_reshape, name, reuse=reuse)
atom_ener_reshape = tf.reshape(atom_ener, [-1, self.natoms[0]])
energy = tf.reduce_sum(atom_ener_reshape, axis=1)
net_deriv_ = tf.gradients(atom_ener, inputs_reshape)
net_deriv = net_deriv_[0]
net_deriv_reshape = tf.reshape(net_deriv,
[-1, self.natoms[0] * self.ndescrpt])
force = op_module.prod_force_se_r(net_deriv_reshape, descrpt_deriv,
nlist, tnatoms)
virial, atom_vir = op_module.prod_virial_se_r(net_deriv_reshape,
descrpt_deriv, rij,
nlist, tnatoms)
return energy, force, virial
def prod_force_virial(self, atom_ener, natoms) :
[net_deriv] = tf.gradients (atom_ener, self.descrpt_reshape)
net_deriv_reshape = tf.reshape (net_deriv, [-1, natoms[0] * self.ndescrpt])
force \
= op_module.prod_force_se_r (net_deriv_reshape,
self.descrpt_deriv,
self.nlist,
natoms)
virial, atom_virial \
= op_module.prod_virial_se_r (net_deriv_reshape,
self.descrpt_deriv,
self.rij,
self.nlist,
natoms)
return force, virial, atom_virial
def prod_force_virial(
self, atom_ener: tf.Tensor,
natoms: tf.Tensor) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor]:
"""
Compute force and virial
Parameters
----------
atom_ener
The atomic energy
natoms
The number of atoms. This tensor has the length of Ntypes + 2
natoms[0]: number of local atoms
natoms[1]: total number of atoms held by this processor
natoms[i]: 2 <= i < Ntypes+2, number of type i atoms
Returns
-------
force
The force on atoms
virial
The total virial
atom_virial
The atomic virial
"""
[net_deriv] = tf.gradients(atom_ener, self.descrpt_reshape)
tf.summary.histogram('net_derivative', net_deriv)
net_deriv_reshape = tf.reshape(net_deriv,
[-1, natoms[0] * self.ndescrpt])
force \
= op_module.prod_force_se_r (net_deriv_reshape,
self.descrpt_deriv,
self.nlist,
natoms)
virial, atom_virial \
= op_module.prod_virial_se_r (net_deriv_reshape,
self.descrpt_deriv,
self.rij,
self.nlist,
natoms)
tf.summary.histogram('force', force)
tf.summary.histogram('virial', virial)
tf.summary.histogram('atom_virial', atom_virial)
return force, virial, atom_virial
