feat(pt/dp): add exponential switch function

deepmd/dpmodel/descriptor/dpa3.py

@@ -123,6 +123,14 @@ class RepFlowArgs:
     smooth_edge_update : bool, optional
         Whether to make edge update smooth.
         If True, the edge update from angle message will not use self as padding.
+    use_exp_switch : bool, optional
+        Whether to use an exponential switch function instead of a polynomial one in the neighbor update.
+        The exponential switch function ensures neighbor contributions smoothly diminish as the interatomic distance
+        `r` approaches the cutoff radius `rcut`. Specifically, the function is defined as:
+        s(r) = \\exp(-\\exp(20 * (r - rcut_smth) / rcut_smth)) for 0 < r \\leq rcut, and s(r) = 0 for r > rcut.
+        Here, `rcut_smth` is an adjustable smoothing factor and `rcut_smth` should be chosen carefully
+        according to `rcut`, ensuring s(r) approaches zero smoothly at the cutoff.
+        Typical recommended values are `rcut_smth` = 5.3 for `rcut` = 6.0, and 3.5 for `rcut` = 4.0.
     use_dynamic_sel : bool, optional
         Whether to dynamically select neighbors within the cutoff radius.
         If True, the exact number of neighbors within the cutoff radius is used
@@ -162,6 +170,7 @@ def __init__(
         skip_stat: bool = False,
         optim_update: bool = True,
         smooth_edge_update: bool = False,
+        use_exp_switch: bool = False,
         use_dynamic_sel: bool = False,
         sel_reduce_factor: float = 10.0,
     ) -> None:
@@ -190,6 +199,7 @@ def __init__(
         self.a_compress_use_split = a_compress_use_split
         self.optim_update = optim_update
         self.smooth_edge_update = smooth_edge_update
+        self.use_exp_switch = use_exp_switch
         self.use_dynamic_sel = use_dynamic_sel
         self.sel_reduce_factor = sel_reduce_factor
 
@@ -223,6 +233,7 @@ def serialize(self) -> dict:
             "fix_stat_std": self.fix_stat_std,
             "optim_update": self.optim_update,
             "smooth_edge_update": self.smooth_edge_update,
+            "use_exp_switch": self.use_exp_switch,
             "use_dynamic_sel": self.use_dynamic_sel,
             "sel_reduce_factor": self.sel_reduce_factor,
         }
@@ -321,6 +332,7 @@ def init_subclass_params(sub_data, sub_class):
             fix_stat_std=self.repflow_args.fix_stat_std,
             optim_update=self.repflow_args.optim_update,
             smooth_edge_update=self.repflow_args.smooth_edge_update,
+            use_exp_switch=self.repflow_args.use_exp_switch,
             use_dynamic_sel=self.repflow_args.use_dynamic_sel,
             sel_reduce_factor=self.repflow_args.sel_reduce_factor,
             exclude_types=exclude_types,

deepmd/dpmodel/descriptor/repflows.py

@@ -125,6 +125,14 @@ class DescrptBlockRepflows(NativeOP, DescriptorBlock):
     smooth_edge_update : bool, optional
         Whether to make edge update smooth.
         If True, the edge update from angle message will not use self as padding.
+    use_exp_switch : bool, optional
+        Whether to use an exponential switch function instead of a polynomial one in the neighbor update.
+        The exponential switch function ensures neighbor contributions smoothly diminish as the interatomic distance
+        `r` approaches the cutoff radius `rcut`. Specifically, the function is defined as:
+        s(r) = \\exp(-\\exp(20 * (r - rcut_smth) / rcut_smth)) for 0 < r \\leq rcut, and s(r) = 0 for r > rcut.
+        Here, `rcut_smth` is an adjustable smoothing factor and `rcut_smth` should be chosen carefully
+        according to `rcut`, ensuring s(r) approaches zero smoothly at the cutoff.
+        Typical recommended values are `rcut_smth` = 5.3 for `rcut` = 6.0, and 3.5 for `rcut` = 4.0.
     use_dynamic_sel : bool, optional
         Whether to dynamically select neighbors within the cutoff radius.
         If True, the exact number of neighbors within the cutoff radius is used
@@ -185,6 +193,7 @@ def __init__(
         fix_stat_std: float = 0.3,
         optim_update: bool = True,
         smooth_edge_update: bool = False,
+        use_exp_switch: bool = False,
         use_dynamic_sel: bool = False,
         sel_reduce_factor: float = 10.0,
         seed: Optional[Union[int, list[int]]] = None,
@@ -218,6 +227,7 @@ def __init__(
         self.a_compress_use_split = a_compress_use_split
         self.optim_update = optim_update
         self.smooth_edge_update = smooth_edge_update
+        self.use_exp_switch = use_exp_switch
         self.use_dynamic_sel = use_dynamic_sel
         self.sel_reduce_factor = sel_reduce_factor
         if self.use_dynamic_sel and not self.smooth_edge_update:
@@ -290,10 +300,16 @@ def __init__(
 
         wanted_shape = (self.ntypes, self.nnei, 4)
         self.env_mat_edge = EnvMat(
-            self.e_rcut, self.e_rcut_smth, protection=self.env_protection
+            self.e_rcut,
+            self.e_rcut_smth,
+            protection=self.env_protection,
+            use_exp_switch=self.use_exp_switch,
         )
         self.env_mat_angle = EnvMat(
-            self.a_rcut, self.a_rcut_smth, protection=self.env_protection
+            self.a_rcut,
+            self.a_rcut_smth,
+            protection=self.env_protection,
+            use_exp_switch=self.use_exp_switch,
         )
         self.mean = np.zeros(wanted_shape, dtype=PRECISION_DICT[self.precision])
         self.stddev = np.ones(wanted_shape, dtype=PRECISION_DICT[self.precision])
@@ -647,6 +663,7 @@ def serialize(self):
             "precision": self.precision,
             "fix_stat_std": self.fix_stat_std,
             "optim_update": self.optim_update,
+            "use_exp_switch": self.use_exp_switch,
             "smooth_edge_update": self.smooth_edge_update,
             "use_dynamic_sel": self.use_dynamic_sel,
             "sel_reduce_factor": self.sel_reduce_factor,

deepmd/dpmodel/utils/env_mat.py

@@ -35,13 +35,32 @@
     return vv
 
 
+@support_array_api(version="2023.12")
+def compute_exp_sw(
+    distance: np.ndarray,
+    rmin: float,
+    rmax: float,
+):
+    """Compute the exponential switch function for neighbor update."""
+    if rmin >= rmax:
+        raise ValueError("rmin should be less than rmax.")
+    xp = array_api_compat.array_namespace(distance)
+    distance = xp.clip(distance, min=0.0, max=rmax)
+    C = 20
+    a = C / rmin
+    b = rmin
+    exp_sw = xp.exp(-xp.exp(a * (distance - b)))
+    return exp_sw
+
+
 def _make_env_mat(
     nlist,
     coord,
     rcut: float,
     ruct_smth: float,
     radial_only: bool = False,
     protection: float = 0.0,
+    use_exp_switch: bool = False,
 ):
     """Make smooth environment matrix."""
     xp = array_api_compat.array_namespace(nlist)
@@ -66,7 +85,11 @@
     length = length + xp.astype(~xp.expand_dims(mask, axis=-1), length.dtype)
     t0 = 1 / (length + protection)
     t1 = diff / (length + protection) ** 2
-    weight = compute_smooth_weight(length, ruct_smth, rcut)
+    weight = (
+        compute_smooth_weight(length, ruct_smth, rcut)
+        if not use_exp_switch
+        else compute_exp_sw(length, ruct_smth, rcut)
+    )
     weight = weight * xp.astype(xp.expand_dims(mask, axis=-1), weight.dtype)
     if radial_only:
         env_mat = t0 * weight
@@ -81,10 +104,12 @@
         rcut,
         rcut_smth,
         protection: float = 0.0,
+        use_exp_switch: bool = False,
     ) -> None:
         self.rcut = rcut
         self.rcut_smth = rcut_smth
         self.protection = protection
+        self.use_exp_switch = use_exp_switch
 
     def call(
         self,
@@ -142,6 +167,7 @@
             self.rcut_smth,
             radial_only=radial_only,
             protection=self.protection,
+            use_exp_switch=self.use_exp_switch,
         )
         return em, diff, ww
 
@@ -151,6 +177,8 @@
         return {
             "rcut": self.rcut,
             "rcut_smth": self.rcut_smth,
+            "protection": self.protection,
+            "use_exp_switch": self.use_exp_switch,
         }
 
     @classmethod

deepmd/pd/model/descriptor/dpa1.py

@@ -506,7 +506,9 @@ def serialize(self) -> dict:
             "precision": RESERVED_PRECISION_DICT[obj.prec],
             "embeddings": obj.filter_layers.serialize(),
             "attention_layers": obj.dpa1_attention.serialize(),
-            "env_mat": DPEnvMat(obj.rcut, obj.rcut_smth).serialize(),
+            "env_mat": DPEnvMat(
+                obj.rcut, obj.rcut_smth, obj.env_protection
+            ).serialize(),
             "type_embedding": self.type_embedding.embedding.serialize(),
             "exclude_types": obj.exclude_types,
             "env_protection": obj.env_protection,

deepmd/pd/model/descriptor/se_a.py

@@ -337,7 +337,9 @@ def serialize(self) -> dict:
             # make deterministic
             "precision": RESERVED_PRECISION_DICT[obj.prec],
             "embeddings": obj.filter_layers.serialize(),
-            "env_mat": DPEnvMat(obj.rcut, obj.rcut_smth).serialize(),
+            "env_mat": DPEnvMat(
+                obj.rcut, obj.rcut_smth, obj.env_protection
+            ).serialize(),
             "exclude_types": obj.exclude_types,
             "env_protection": obj.env_protection,
             "@variables": {

deepmd/pt/model/descriptor/dpa1.py

@@ -508,7 +508,9 @@ def serialize(self) -> dict:
             "precision": RESERVED_PRECISION_DICT[obj.prec],
             "embeddings": obj.filter_layers.serialize(),
             "attention_layers": obj.dpa1_attention.serialize(),
-            "env_mat": DPEnvMat(obj.rcut, obj.rcut_smth).serialize(),
+            "env_mat": DPEnvMat(
+                obj.rcut, obj.rcut_smth, obj.env_protection
+            ).serialize(),
             "type_embedding": self.type_embedding.embedding.serialize(),
             "exclude_types": obj.exclude_types,
             "env_protection": obj.env_protection,

deepmd/pt/model/descriptor/dpa3.py

@@ -150,6 +150,7 @@ def init_subclass_params(sub_data, sub_class):
             fix_stat_std=self.repflow_args.fix_stat_std,
             optim_update=self.repflow_args.optim_update,
             smooth_edge_update=self.repflow_args.smooth_edge_update,
+            use_exp_switch=self.repflow_args.use_exp_switch,
             use_dynamic_sel=self.repflow_args.use_dynamic_sel,
             sel_reduce_factor=self.repflow_args.sel_reduce_factor,
             exclude_types=exclude_types,

deepmd/pt/model/descriptor/env_mat.py

@@ -3,6 +3,7 @@
 import torch
 
 from deepmd.pt.utils.preprocess import (
+    compute_exp_sw,
     compute_smooth_weight,
 )
 
@@ -14,6 +15,7 @@ def _make_env_mat(
     ruct_smth: float,
     radial_only: bool = False,
     protection: float = 0.0,
+    use_exp_switch: bool = False,
 ):
     """Make smooth environment matrix."""
     bsz, natoms, nnei = nlist.shape
@@ -33,7 +35,11 @@ def _make_env_mat(
     length = length + ~mask.unsqueeze(-1)
     t0 = 1 / (length + protection)
     t1 = diff / (length + protection) ** 2
-    weight = compute_smooth_weight(length, ruct_smth, rcut)
+    weight = (
+        compute_smooth_weight(length, ruct_smth, rcut)
+        if not use_exp_switch
+        else compute_exp_sw(length, ruct_smth, rcut)
+    )
     weight = weight * mask.unsqueeze(-1)
     if radial_only:
         env_mat = t0 * weight
@@ -52,6 +58,7 @@ def prod_env_mat(
     rcut_smth: float,
     radial_only: bool = False,
     protection: float = 0.0,
+    use_exp_switch: bool = False,
 ):
     """Generate smooth environment matrix from atom coordinates and other context.
 
@@ -64,6 +71,7 @@ def prod_env_mat(
     - rcut_smth: Smooth hyper-parameter for pair force & energy.
     - radial_only: Whether to return a full description or a radial-only descriptor.
     - protection: Protection parameter to prevent division by zero errors during calculations.
+    - use_exp_switch: Whether to use the exponential switch function.
 
     Returns
     -------
@@ -76,6 +84,7 @@ def prod_env_mat(
         rcut_smth,
         radial_only,
         protection=protection,
+        use_exp_switch=use_exp_switch,
     )  # shape [n_atom, dim, 4 or 1]
     t_avg = mean[atype]  # [n_atom, dim, 4 or 1]
     t_std = stddev[atype]  # [n_atom, dim, 4 or 1]

deepmd/pt/model/descriptor/repflows.py

@@ -136,6 +136,14 @@ class DescrptBlockRepflows(DescriptorBlock):
     smooth_edge_update : bool, optional
         Whether to make edge update smooth.
         If True, the edge update from angle message will not use self as padding.
+    use_exp_switch : bool, optional
+        Whether to use an exponential switch function instead of a polynomial one in the neighbor update.
+        The exponential switch function ensures neighbor contributions smoothly diminish as the interatomic distance
+        `r` approaches the cutoff radius `rcut`. Specifically, the function is defined as:
+        s(r) = \\exp(-\\exp(20 * (r - rcut_smth) / rcut_smth)) for 0 < r \\leq rcut, and s(r) = 0 for r > rcut.
+        Here, `rcut_smth` is an adjustable smoothing factor and `rcut_smth` should be chosen carefully
+        according to `rcut`, ensuring s(r) approaches zero smoothly at the cutoff.
+        Typical recommended values are `rcut_smth` = 5.3 for `rcut` = 6.0, and 3.5 for `rcut` = 4.0.
     use_dynamic_sel : bool, optional
         Whether to dynamically select neighbors within the cutoff radius.
         If True, the exact number of neighbors within the cutoff radius is used
@@ -198,6 +206,7 @@ def __init__(
         precision: str = "float64",
         fix_stat_std: float = 0.3,
         smooth_edge_update: bool = False,
+        use_exp_switch: bool = False,
         use_dynamic_sel: bool = False,
         sel_reduce_factor: float = 10.0,
         optim_update: bool = True,
@@ -232,6 +241,7 @@ def __init__(
         self.a_compress_use_split = a_compress_use_split
         self.optim_update = optim_update
         self.smooth_edge_update = smooth_edge_update
+        self.use_exp_switch = use_exp_switch
         self.use_dynamic_sel = use_dynamic_sel
         self.sel_reduce_factor = sel_reduce_factor
         if self.use_dynamic_sel and not self.smooth_edge_update:
@@ -425,6 +435,7 @@ def forward(
             self.e_rcut,
             self.e_rcut_smth,
             protection=self.env_protection,
+            use_exp_switch=self.use_exp_switch,
         )
         nlist_mask = nlist != -1
         sw = torch.squeeze(sw, -1)
@@ -446,6 +457,7 @@ def forward(
             self.a_rcut,
             self.a_rcut_smth,
             protection=self.env_protection,
+            use_exp_switch=self.use_exp_switch,
         )
         a_nlist_mask = a_nlist != -1
         a_sw = torch.squeeze(a_sw, -1)

deepmd/pt/model/descriptor/se_a.py

@@ -381,7 +381,9 @@ def serialize(self) -> dict:
             # make deterministic
             "precision": RESERVED_PRECISION_DICT[obj.prec],
             "embeddings": obj.filter_layers.serialize(),
-            "env_mat": DPEnvMat(obj.rcut, obj.rcut_smth).serialize(),
+            "env_mat": DPEnvMat(
+                obj.rcut, obj.rcut_smth, obj.env_protection
+            ).serialize(),
             "exclude_types": obj.exclude_types,
             "env_protection": obj.env_protection,
             "@variables": {

deepmd/pt/model/descriptor/se_t.py

@@ -415,7 +415,9 @@ def serialize(self) -> dict:
             "activation_function": obj.activation_function,
             "precision": RESERVED_PRECISION_DICT[obj.prec],
             "embeddings": obj.filter_layers.serialize(),
-            "env_mat": DPEnvMat(obj.rcut, obj.rcut_smth).serialize(),
+            "env_mat": DPEnvMat(
+                obj.rcut, obj.rcut_smth, obj.env_protection
+            ).serialize(),
             "exclude_types": obj.exclude_types,
             "env_protection": obj.env_protection,
             "type_map": self.type_map,

deepmd/pt/utils/preprocess.py

@@ -15,3 +15,15 @@ def compute_smooth_weight(distance, rmin: float, rmax: float):
     uu2 = uu * uu
     vv = uu2 * uu * (-6 * uu2 + 15 * uu - 10) + 1
     return vv
+
+
+def compute_exp_sw(distance, rmin: float, rmax: float):
+    """Compute the exponential switch function for neighbor update."""
+    if rmin >= rmax:
+        raise ValueError("rmin should be less than rmax.")
+    distance = torch.clamp(distance, min=0.0, max=rmax)
+    C = 20
+    a = C / rmin
+    b = rmin
+    exp_sw = torch.exp(-torch.exp(a * (distance - b)))
+    return exp_sw

deepmd/utils/argcheck.py

@@ -1497,6 +1497,15 @@ def dpa3_repflow_args():
         "Whether to make edge update smooth. "
         "If True, the edge update from angle message will not use self as padding."
     )
+    doc_use_exp_switch = (
+        "Whether to use an exponential switch function instead of a polynomial one in the neighbor update. "
+        "The exponential switch function ensures neighbor contributions smoothly diminish as the interatomic distance "
+        "`r` approaches the cutoff radius `rcut`. Specifically, the function is defined as: "
+        "s(r) = \\exp(-\\exp(20 * (r - rcut_smth) / rcut_smth)) for 0 < r \\leq rcut, and s(r) = 0 for r > rcut. "
+        "Here, `rcut_smth` is an adjustable smoothing factor and should be chosen carefully according to `rcut`, "
+        "ensuring s(r) approaches zero smoothly at the cutoff. "
+        "Typical recommended values are `rcut_smth` = 5.3 for `rcut` = 6.0, and 3.5 for `rcut` = 4.0."
+    )
     doc_use_dynamic_sel = (
         "Whether to dynamically select neighbors within the cutoff radius. "
         "If True, the exact number of neighbors within the cutoff radius is used "
@@ -1611,6 +1620,14 @@ def dpa3_repflow_args():
             default=False,  # For compatability. This will be True in the future
             doc=doc_smooth_edge_update,
         ),
+        Argument(
+            "use_exp_switch",
+            bool,
+            optional=True,
+            default=False,
+            alias=["use_env_envelope"],
+            doc=doc_use_exp_switch,
+        ),
         Argument(
             "use_dynamic_sel",
             bool,