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raise warning before training if sel is not enough #914

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Aug 2, 2021
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raise warning before training if sel is not enough #914

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15 changes: 13 additions & 2 deletions deepmd/entrypoints/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -276,11 +276,22 @@ def wrap_up_4(xx):


def update_one_sel(jdata, descriptor):
rcut = descriptor['rcut']
tmp_sel = get_sel(jdata, rcut)
if parse_auto_sel(descriptor['sel']) :
ratio = parse_auto_sel_ratio(descriptor['sel'])
rcut = descriptor['rcut']
tmp_sel = get_sel(jdata, rcut)
descriptor['sel'] = [int(wrap_up_4(ii * ratio)) for ii in tmp_sel]
else:
# sel is set by user
for ii, (tt, dd) in enumerate(zip(tmp_sel, descriptor['sel'])):
if dd and tt > dd:
# we may skip warning for sel=0, where the user is likely
# to exclude such type in the descriptor
log.warning(
"sel of type %d is not enough! The expected value is "
"not less than %d, but you set it to %d. The accuracy"
" of your model may get worse." %(ii, tt, dd)
)
return descriptor


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7 changes: 7 additions & 0 deletions deepmd/utils/neighbor_stat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,6 +89,13 @@ def get_stat(self,
log.warning("Atoms with no neighbors found in %s. Please make sure it's what you expected."%jj)

if dt < self.min_nbor_dist:
if math.isclose(dt, 0., rel_tol=1e-6):
# it's unexpected that the distance between two atoms is zero
# zero distance will cause nan (#874)
raise RuntimeError(
"Some atoms in %s are overlapping. Please check your"
" training data to remove duplicated atoms." % jj
)
self.min_nbor_dist = dt
for ww in range(self.ntypes):
var = np.max(mn[:, ww])
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