diff --git a/deepmd/tf/infer/deep_eval.py b/deepmd/tf/infer/deep_eval.py index d594a47115..a7682d2e58 100644 --- a/deepmd/tf/infer/deep_eval.py +++ b/deepmd/tf/infer/deep_eval.py @@ -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() else: self.modifier_type = None @@ -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): 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 + ) return output_dict def _prepare_feed_dict( @@ -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] if sel_atoms is not None: selection = [False] * np.size(atom_type) for ii in sel_atoms: diff --git a/source/lmp/tests/lrdipole.pbtxt b/source/lmp/tests/lrdipole.pbtxt new file mode 100644 index 0000000000..5d7635ae18 --- /dev/null +++ b/source/lmp/tests/lrdipole.pbtxt @@ -0,0 +1,52510 @@ +node { + name: 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b/source/tests/tf/test_dplr.py index 195b1d0820..cf9ab1d392 100644 --- a/source/tests/tf/test_dplr.py +++ b/source/tests/tf/test_dplr.py @@ -9,6 +9,9 @@ from deepmd.infer.deep_pot import ( DeepPot, ) +from deepmd.tf.common import ( + clear_session, +) from deepmd.tf.utils.convert import ( convert_pbtxt_to_pb, ) @@ -16,21 +19,26 @@ class TestDPLR(unittest.TestCase): def setUp(self) -> None: + clear_session() # a bit strange path, need to move to the correct directory pbtxt_file = ( Path(__file__).parent.parent.parent / "lmp" / "tests" / "lrmodel.pbtxt" ) convert_pbtxt_to_pb(pbtxt_file, "lrmodel.pb") + pbtxt_file = ( + Path(__file__).parent.parent.parent / "lmp" / "tests" / "lrdipole.pbtxt" + ) + convert_pbtxt_to_pb(pbtxt_file, "lrdipole.pb") - self.expected_e_lr_efield_variable = -40.56538550 + self.expected_e_lr_efield_variable = -35.713836 self.expected_f_lr_efield_variable = np.array( [ - [0.35019748, 0.27802691, -0.38443156], - [-0.42115581, -0.20474826, -0.02701100], - [-0.56357653, 0.34154004, 0.78389512], - [0.21023870, -0.60684635, -0.39875165], - [0.78732106, 0.00610023, 0.17197636], - [-0.36302488, 0.18592742, -0.14567727], + [1.479351, 0.430085, 2.234422], + [-1.636212, 1.001423, 5.771218], + [-1.046306, 5.068619, 0.037626], + [1.043115, -0.01208, -3.296184], + [1.819341, -4.589436, -1.725136], + [-1.659289, -1.898612, -3.021946], ] ) @@ -51,9 +59,7 @@ def setUp(self) -> None: def test_eval(self) -> None: dp = DeepPot("lrmodel.pb") - e, f, v, ae, av = dp.eval( - self.coord[:, :6], self.box, self.atype[:6], atomic=True - ) + e, f, v = dp.eval(self.coord[:, :6], self.box, self.atype[:6], atomic=False) np.testing.assert_allclose(e, self.expected_e_lr_efield_variable, atol=1e-6) np.testing.assert_allclose( f.ravel(), self.expected_f_lr_efield_variable.ravel(), atol=1e-6