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add atom energy bias to type embedding energy #1592

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merged 3 commits into from
Mar 25, 2022
Merged

add atom energy bias to type embedding energy #1592

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2a81572
add atom energy bias to type embedding energy
njzjz Mar 24, 2022
88529f5
looks like tf.repeat is unavaiable in old TF...
njzjz Mar 24, 2022
c91bad6
add statement `self.bias_atom_e is not None`
njzjz Mar 24, 2022
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8 changes: 7 additions & 1 deletion deepmd/fit/ener.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
import warnings
import numpy as np
from typing import Tuple, List
from packaging.version import Version

from deepmd.env import tf
from deepmd.common import add_data_requirement, get_activation_func, get_precision, ACTIVATION_FN_DICT, PRECISION_DICT, docstring_parameter, cast_precision
Expand All @@ -11,7 +12,7 @@
from deepmd.fit.fitting import Fitting

from deepmd.env import global_cvt_2_tf_float
from deepmd.env import GLOBAL_TF_FLOAT_PRECISION
from deepmd.env import GLOBAL_TF_FLOAT_PRECISION, TF_VERSION

class EnerFitting (Fitting):
r"""Fitting the energy of the system. The force and the virial can also be trained.
Expand Down Expand Up @@ -490,6 +491,11 @@ def build (self,
bias_atom_e=0.0, suffix=suffix, reuse=reuse
)
outs = tf.reshape(final_layer, [tf.shape(inputs)[0], natoms[0]])
# add atom energy bias; TF will broadcast to all batches
# tf.repeat is avaiable in TF>=2.1 or TF 1.15
_TF_VERSION = Version(TF_VERSION)
if (Version('1.15') <= _TF_VERSION < Version('2') or _TF_VERSION >= Version('2.1')) and self.bias_atom_e is not None:
outs += tf.repeat(tf.constant(self.bias_atom_e, dtype=self.fitting_precision), natoms[2:])

if self.tot_ener_zero:
force_tot_ener = 0.0
Expand Down