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fix(tf): fix dplr Python inference #4753

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Merged
njzjz merged 2 commits into from
May 21, 2025
Merged

fix(tf): fix dplr Python inference #4753

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60fe66e
fix(tf): fix dplr Python inference
njzjz May 20, 2025
b99f80b
reset states before test
njzjz May 21, 2025
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20 changes: 13 additions & 7 deletions deepmd/tf/infer/deep_eval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -259,7 +259,9 @@ def _init_attr(self) -> None:
self.numb_dos = 0
self.tmap = tmap.decode("utf-8").split()
if self.tensors["modifier_type"] is not None:
self.modifier_type = run_sess(self.sess, [self.tensors["modifier_type"]])[0]
self.modifier_type = run_sess(self.sess, [self.tensors["modifier_type"]])[
0
].decode()
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else:
self.modifier_type = None

Expand Down Expand Up @@ -761,15 +763,17 @@ def eval(
odef.name: oo for oo, odef in zip(output, self.output_def.var_defs.values())
}
# ugly!!
if self.modifier_type is not None and isinstance(self.model_type, DeepPot):
if self.modifier_type is not None and issubclass(self.model_type, DeepPot):
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if atomic:
raise RuntimeError("modifier does not support atomic modification")
me, mf, mv = self.dm.eval(coords, cells, atom_types)
output = list(output) # tuple to list
e, f, v = output[:3]
output_dict["energy_redu"] += me.reshape(e.shape)
output_dict["energy_deri_r"] += mf.reshape(f.shape)
output_dict["energy_deri_c_redu"] += mv.reshape(v.shape)
output_dict["energy_redu"] += me.reshape(output_dict["energy_redu"].shape)
output_dict["energy_derv_r"] += mf.reshape(
output_dict["energy_derv_r"].shape
)
output_dict["energy_derv_c_redu"] += mv.reshape(
output_dict["energy_derv_c_redu"].shape
)
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return output_dict

def _prepare_feed_dict(
Expand Down Expand Up @@ -1348,6 +1352,8 @@ def sort_input(
natoms = atom_type[0].size
idx_map = np.arange(natoms) # pylint: disable=no-explicit-dtype
return coord, atom_type, idx_map
if atom_type.ndim > 1:
atom_type = atom_type[0]
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if sel_atoms is not None:
selection = [False] * np.size(atom_type)
for ii in sel_atoms:
Expand Down
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