rename and add uts

Author: iProzd

deepmd/dpmodel/descriptor/dpa3.py

@@ -15,7 +15,6 @@ def __init__(
         a_rcut_smth: float = 3.5,
         a_sel: int = 20,
         axis_neuron: int = 4,
-        node_has_conv: bool = False,
         update_angle: bool = True,
         update_style: str = "res_residual",
         update_residual: float = 0.1,
@@ -73,7 +72,6 @@ def __init__(
         self.a_rcut_smth = a_rcut_smth
         self.a_sel = a_sel
         self.axis_neuron = axis_neuron
-        self.node_has_conv = node_has_conv  # tmp
         self.update_angle = update_angle
         self.update_style = update_style
         self.update_residual = update_residual
@@ -98,7 +96,6 @@ def serialize(self) -> dict:
             "a_rcut_smth": self.a_rcut_smth,
             "a_sel": self.a_sel,
             "axis_neuron": self.axis_neuron,
-            "node_has_conv": self.node_has_conv,  # tmp
             "update_angle": self.update_angle,
             "update_style": self.update_style,
             "update_residual": self.update_residual,

deepmd/pt/model/descriptor/dpa3.py

@@ -152,7 +152,6 @@ def init_subclass_params(sub_data, sub_class):
             e_dim=self.repflow_args.e_dim,
             a_dim=self.repflow_args.a_dim,
             axis_neuron=self.repflow_args.axis_neuron,
-            node_has_conv=self.repflow_args.node_has_conv,
             update_angle=self.repflow_args.update_angle,
             activation_function=self.activation_function,
             update_style=self.repflow_args.update_style,
@@ -299,7 +298,7 @@ def change_type_map(
             extend_descrpt_stat(
                 repflow,
                 type_map,
-                des_with_stat=model_with_new_type_stat.repflow
+                des_with_stat=model_with_new_type_stat.repflows
                 if model_with_new_type_stat is not None
                 else None,
             )
@@ -380,6 +379,7 @@ def serialize(self) -> dict:
         }
         repflow_variable = {
             "edge_embd": repflows.edge_embd.serialize(),
+            "angle_embd": repflows.angle_embd.serialize(),
             "repflow_layers": [layer.serialize() for layer in repflows.layers],
             "env_mat": DPEnvMat(repflows.rcut, repflows.rcut_smth).serialize(),
             "@variables": {
@@ -417,6 +417,9 @@ def t_cvt(xx):
         env_mat = repflow_variable.pop("env_mat")
         repflow_layers = repflow_variable.pop("repflow_layers")
         obj.repflows.edge_embd = MLPLayer.deserialize(repflow_variable.pop("edge_embd"))
+        obj.repflows.angle_embd = MLPLayer.deserialize(
+            repflow_variable.pop("angle_embd")
+        )
         obj.repflows["davg"] = t_cvt(statistic_repflows["davg"])
         obj.repflows["dstd"] = t_cvt(statistic_repflows["dstd"])
         obj.repflows.layers = torch.nn.ModuleList(
@@ -449,12 +452,12 @@ def forward(
 
         Returns
         -------
-        node_embd
+        node_ebd
             The output descriptor. shape: nf x nloc x n_dim (or n_dim + tebd_dim)
         rot_mat
             The rotationally equivariant and permutationally invariant single particle
             representation. shape: nf x nloc x e_dim x 3
-        edge_embd
+        edge_ebd
             The edge embedding.
             shape: nf x nloc x nnei x e_dim
         h2
@@ -469,23 +472,23 @@ def forward(
         nframes, nloc, nnei = nlist.shape
         nall = extended_coord.view(nframes, -1).shape[1] // 3
 
-        node_embd_ext = self.type_embedding(extended_atype)
-        node_embd_inp = node_embd_ext[:, :nloc, :]
+        node_ebd_ext = self.type_embedding(extended_atype)
+        node_ebd_inp = node_ebd_ext[:, :nloc, :]
         # repflows
-        node_embd, edge_embd, h2, rot_mat, sw = self.repflows(
+        node_ebd, edge_ebd, h2, rot_mat, sw = self.repflows(
             nlist,
             extended_coord,
             extended_atype,
-            node_embd_ext,
+            node_ebd_ext,
             mapping,
             comm_dict=comm_dict,
         )
         if self.concat_output_tebd:
-            node_embd = torch.cat([node_embd, node_embd_inp], dim=-1)
+            node_ebd = torch.cat([node_ebd, node_ebd_inp], dim=-1)
         return (
-            node_embd.to(dtype=env.GLOBAL_PT_FLOAT_PRECISION),
+            node_ebd.to(dtype=env.GLOBAL_PT_FLOAT_PRECISION),
             rot_mat.to(dtype=env.GLOBAL_PT_FLOAT_PRECISION),
-            edge_embd.to(dtype=env.GLOBAL_PT_FLOAT_PRECISION),
+            edge_ebd.to(dtype=env.GLOBAL_PT_FLOAT_PRECISION),
             h2.to(dtype=env.GLOBAL_PT_FLOAT_PRECISION),
             sw.to(dtype=env.GLOBAL_PT_FLOAT_PRECISION),
         )