fix conversion of type_map

Author: HydrogenSulfate

deepmd/pd/model/atomic_model/base_atomic_model.py

@@ -84,9 +84,11 @@ def __init__(
         paddle.nn.Layer.__init__(self)
         BaseAtomicModel_.__init__(self)
         self.type_map = type_map
-        self.register_buffer(
-            "buffer_type_map", paddle.to_tensor([ord(c) for c in type_map])
-        )
+        if type_map is not None:
+            self.register_buffer(
+                "buffer_type_map",
+                paddle.to_tensor([ord(c) for c in " ".join(type_map)]),
+            )
         self.ntypes = len(self.type_map)
         self.register_buffer(
             "buffer_ntypes", paddle.to_tensor(self.ntypes, dtype="int64")

deepmd/pd/model/descriptor/dpa1.py

@@ -297,9 +297,11 @@ def __init__(
         self.use_econf_tebd = use_econf_tebd
         self.use_tebd_bias = use_tebd_bias
         self.type_map = type_map
-        self.register_buffer(
-            "buffer_type_map", paddle.to_tensor([ord(c) for c in type_map])
-        )
+        if type_map is not None:
+            self.register_buffer(
+                "buffer_type_map",
+                paddle.to_tensor([ord(c) for c in " ".join(type_map)]),
+            )
         self.compress = False
         self.type_embedding = TypeEmbedNet(
             ntypes,

deepmd/pd/model/descriptor/dpa2.py

@@ -265,9 +265,11 @@ def init_subclass_params(sub_data, sub_class):
         self.use_econf_tebd = use_econf_tebd
         self.use_tebd_bias = use_tebd_bias
         self.type_map = type_map
-        self.register_buffer(
-            "buffer_type_map", paddle.to_tensor([ord(c) for c in type_map])
-        )
+        if type_map is not None:
+            self.register_buffer(
+                "buffer_type_map",
+                paddle.to_tensor([ord(c) for c in " ".join(type_map)]),
+            )
         self.type_embedding = TypeEmbedNet(
             ntypes,
             self.repinit_args.tebd_dim,

deepmd/pd/model/descriptor/dpa3.py

@@ -178,7 +178,7 @@ def init_subclass_params(sub_data, sub_class):
         self.type_map = type_map
         self.register_buffer(
             "buffer_type_map",
-            paddle.to_tensor([ord(c) for c in self.type_map]),
+            paddle.to_tensor([ord(c) for c in " ".join(self.type_map)]),
         )
         self.tebd_dim = self.repflow_args.n_dim
         self.type_embedding = TypeEmbedNet(

deepmd/pd/model/descriptor/se_a.py

@@ -95,9 +95,11 @@ def __init__(
             raise NotImplementedError("old implementation of spin is not supported.")
         super().__init__()
         self.type_map = type_map
-        self.register_buffer(
-            "buffer_type_map", paddle.to_tensor([ord(c) for c in type_map])
-        )
+        if type_map is not None:
+            self.register_buffer(
+                "buffer_type_map",
+                paddle.to_tensor([ord(c) for c in " ".join(type_map)]),
+            )
         self.compress = False
         self.prec = PRECISION_DICT[precision]
         self.sea = DescrptBlockSeA(

deepmd/pd/model/descriptor/se_t_tebd.py

@@ -165,9 +165,11 @@ def __init__(
         self.prec = PRECISION_DICT[precision]
         self.use_econf_tebd = use_econf_tebd
         self.type_map = type_map
-        self.register_buffer(
-            "buffer_type_map", paddle.to_tensor([ord(c) for c in type_map])
-        )
+        if type_map is not None:
+            self.register_buffer(
+                "buffer_type_map",
+                paddle.to_tensor([ord(c) for c in " ".join(type_map)]),
+            )
         self.smooth = smooth
         self.type_embedding = TypeEmbedNet(
             ntypes,

deepmd/pd/model/task/fitting.py

@@ -263,10 +263,11 @@ def __init__(
         self.rcond = rcond
         self.seed = seed
         self.type_map = type_map
-        self.register_buffer(
-            "buffer_type_map",
-            paddle.to_tensor([ord(c) for c in self.type_map]),
-        )
+        if type_map is not None:
+            self.register_buffer(
+                "buffer_type_map",
+                paddle.to_tensor([ord(c) for c in " ".join(self.type_map)]),
+            )
         self.use_aparam_as_mask = use_aparam_as_mask
         # order matters, should be place after the assignment of ntypes
         self.reinit_exclude(exclude_types)