chore: replace reduciable with reducible (deepmodeling#3888)

Fix the spelling as suggested by
deepmodeling#3867 (comment).

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

- **Bug Fixes**
- Corrected typos in attribute names from `reduciable` to `reducible`
across multiple files, enhancing the accuracy of parameter definitions
and improving code consistency.

- **Tests**
- Updated test cases to reflect the corrected attribute names, ensuring
that tests accurately validate the new `reducible` parameter.

These changes improve the clarity and correctness of the codebase,
ensuring that attribute names are consistent and accurately reflect
their intended functionality.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

Signed-off-by: Jinzhe Zeng <[email protected]>

deepmd/dpmodel/atomic_model/base_atomic_model.py

@@ -111,7 +111,7 @@ def atomic_output_def(self) -> FittingOutputDef:
                 OutputVariableDef(
                     name="mask",
                     shape=[1],
-                    reduciable=False,
+                    reducible=False,
                     r_differentiable=False,
                     c_differentiable=False,
                 )

deepmd/dpmodel/atomic_model/linear_atomic_model.py

@@ -243,7 +243,7 @@ def fitting_output_def(self) -> FittingOutputDef:
                 OutputVariableDef(
                     name="energy",
                     shape=[1],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=True,
                     c_differentiable=True,
                 )

deepmd/dpmodel/atomic_model/pairtab_atomic_model.py

@@ -99,7 +99,7 @@ def fitting_output_def(self) -> FittingOutputDef:
                 OutputVariableDef(
                     name="energy",
                     shape=[1],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=True,
                     c_differentiable=True,
                 )

deepmd/dpmodel/fitting/dipole_fitting.py

@@ -77,10 +77,10 @@ class DipoleFitting(GeneralFitting):
             Atomic contributions of the excluded atom types are set zero.
     r_differentiable
             If the variable is differentiated with respect to coordinates of atoms.
-            Only reduciable variable are differentiable.
+            Only reducible variable are differentiable.
     c_differentiable
             If the variable is differentiated with respect to the cell tensor (pbc case).
-            Only reduciable variable are differentiable.
+            Only reducible variable are differentiable.
     type_map: List[str], Optional
             A list of strings. Give the name to each type of atoms.
     """
@@ -173,7 +173,7 @@ def output_def(self):
                 OutputVariableDef(
                     self.var_name,
                     [3],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=self.r_differentiable,
                     c_differentiable=self.c_differentiable,
                 ),

deepmd/dpmodel/fitting/invar_fitting.py

@@ -201,7 +201,7 @@ def output_def(self):
                 OutputVariableDef(
                     self.var_name,
                     [self.dim_out],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=True,
                     c_differentiable=True,
                 ),

deepmd/dpmodel/fitting/polarizability_fitting.py

@@ -216,7 +216,7 @@ def output_def(self):
                 OutputVariableDef(
                     "polarizability",
                     [3, 3],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=False,
                     c_differentiable=False,
                 ),

deepmd/dpmodel/model/transform_output.py

@@ -31,7 +31,7 @@ def fit_output_to_model_output(
         vdef = fit_output_def[kk]
         shap = vdef.shape
         atom_axis = -(len(shap) + 1)
-        if vdef.reduciable:
+        if vdef.reducible:
             kk_redu = get_reduce_name(kk)
             # cast to energy prec brefore reduction
             model_ret[kk_redu] = np.sum(
@@ -63,7 +63,7 @@ def communicate_extended_output(
         vv = model_ret[kk]
         vdef = model_output_def[kk]
         new_ret[kk] = vv
-        if vdef.reduciable:
+        if vdef.reducible:
             kk_redu = get_reduce_name(kk)
             new_ret[kk_redu] = model_ret[kk_redu]
             if vdef.r_differentiable:

deepmd/dpmodel/output_def.py

@@ -65,7 +65,7 @@ def __call__(
             for kk in self.md.keys_outp():
                 dd = self.md[kk]
                 check_var(ret[kk], dd)
-                if dd.reduciable:
+                if dd.reducible:
                     rk = get_reduce_name(kk)
                     check_var(ret[rk], self.md[rk])
                 if dd.r_differentiable:
@@ -166,15 +166,15 @@ class OutputVariableDef:
     shape
           The shape of the variable. e.g. energy should be [1],
           dipole should be [3], polarizabilty should be [3,3].
-    reduciable
+    reducible
           If the variable is reduced.
     r_differentiable
           If the variable is differentiated with respect to coordinates
-          of atoms. Only reduciable variable are differentiable.
+          of atoms. Only reducible variable are differentiable.
           Negative derivative w.r.t. coordinates will be calcualted. (e.g. force)
     c_differentiable
           If the variable is differentiated with respect to the
-          cell tensor (pbc case). Only reduciable variable
+          cell tensor (pbc case). Only reducible variable
           are differentiable.
           Virial, the transposed negative gradient with cell tensor times
           cell tensor, will be calculated, see eq 40 JCP 159, 054801 (2023).
@@ -192,7 +192,7 @@ def __init__(
         self,
         name: str,
         shape: List[int],
-        reduciable: bool = False,
+        reducible: bool = False,
         r_differentiable: bool = False,
         c_differentiable: bool = False,
         atomic: bool = True,
@@ -208,19 +208,19 @@ def __init__(
         for i in range(len_shape):
             self.output_size *= self.shape[i]
         self.atomic = atomic
-        self.reduciable = reduciable
+        self.reducible = reducible
         self.r_differentiable = r_differentiable
         self.c_differentiable = c_differentiable
         if self.c_differentiable and not self.r_differentiable:
             raise ValueError("c differentiable requires r_differentiable")
-        if self.reduciable and not self.atomic:
-            raise ValueError("a reduciable variable should be atomic")
+        if self.reducible and not self.atomic:
+            raise ValueError("a reducible variable should be atomic")
         self.category = category
         self.r_hessian = r_hessian
         self.magnetic = magnetic
         if self.r_hessian:
-            if not self.reduciable:
-                raise ValueError("only reduciable variable can calculate hessian")
+            if not self.reducible:
+                raise ValueError("only reducible variable can calculate hessian")
             if not self.r_differentiable:
                 raise ValueError("only r_differentiable variable can calculate hessian")
 
@@ -407,12 +407,12 @@ def do_reduce(
 ) -> Dict[str, OutputVariableDef]:
     def_redu: Dict[str, OutputVariableDef] = {}
     for kk, vv in def_outp_data.items():
-        if vv.reduciable:
+        if vv.reducible:
             rk = get_reduce_name(kk)
             def_redu[rk] = OutputVariableDef(
                 rk,
                 vv.shape,
-                reduciable=False,
+                reducible=False,
                 r_differentiable=False,
                 c_differentiable=False,
                 atomic=False,
@@ -429,7 +429,7 @@ def do_mask(
     def_mask["mask"] = OutputVariableDef(
         name="mask",
         shape=[1],
-        reduciable=False,
+        reducible=False,
         r_differentiable=False,
         c_differentiable=False,
     )
@@ -439,7 +439,7 @@ def do_mask(
             def_mask["mask_mag"] = OutputVariableDef(
                 name="mask_mag",
                 shape=[1],
-                reduciable=False,
+                reducible=False,
                 r_differentiable=False,
                 c_differentiable=False,
             )
@@ -458,7 +458,7 @@ def do_derivative(
             def_derv_r[rkr] = OutputVariableDef(
                 rkr,
                 vv.shape + [3],  # noqa: RUF005
-                reduciable=False,
+                reducible=False,
                 r_differentiable=(
                     vv.r_hessian and vv.category == OutputVariableCategory.OUT.value
                 ),
@@ -470,7 +470,7 @@ def do_derivative(
                 def_derv_r[rkrm] = OutputVariableDef(
                     rkrm,
                     vv.shape + [3],  # noqa: RUF005
-                    reduciable=False,
+                    reducible=False,
                     r_differentiable=(
                         vv.r_hessian and vv.category == OutputVariableCategory.OUT.value
                     ),
@@ -485,7 +485,7 @@ def do_derivative(
             def_derv_c[rkc] = OutputVariableDef(
                 rkc,
                 vv.shape + [9],  # noqa: RUF005
-                reduciable=True,
+                reducible=True,
                 r_differentiable=False,
                 c_differentiable=False,
                 atomic=True,
@@ -495,7 +495,7 @@ def do_derivative(
                 def_derv_r[rkcm] = OutputVariableDef(
                     rkcm,
                     vv.shape + [9],  # noqa: RUF005
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=False,
                     c_differentiable=False,
                     atomic=True,

deepmd/infer/deep_dos.py

@@ -48,7 +48,7 @@ def output_def(self) -> ModelOutputDef:
                     OutputVariableDef(
                         "dos",
                         shape=[-1],
-                        reduciable=True,
+                        reducible=True,
                         atomic=True,
                     ),
                 ]

deepmd/infer/deep_polar.py

@@ -112,7 +112,7 @@ def output_def(self) -> ModelOutputDef:
                     OutputVariableDef(
                         self.output_tensor_name,
                         shape=[-1],
-                        reduciable=False,
+                        reducible=False,
                         r_differentiable=False,
                         c_differentiable=False,
                         atomic=False,

deepmd/infer/deep_pot.py

@@ -62,7 +62,7 @@ def output_def(self) -> ModelOutputDef:
                     OutputVariableDef(
                         "energy",
                         shape=[1],
-                        reduciable=True,
+                        reducible=True,
                         r_differentiable=True,
                         c_differentiable=True,
                         atomic=True,
@@ -80,7 +80,7 @@ def output_def_mag(self) -> ModelOutputDef:
                     OutputVariableDef(
                         "energy",
                         shape=[1],
-                        reduciable=True,
+                        reducible=True,
                         r_differentiable=True,
                         c_differentiable=True,
                         atomic=True,

deepmd/infer/deep_tensor.py

@@ -226,7 +226,7 @@ def output_def(self) -> ModelOutputDef:
                     OutputVariableDef(
                         self.output_tensor_name,
                         shape=[-1],
-                        reduciable=True,
+                        reducible=True,
                         r_differentiable=True,
                         c_differentiable=True,
                         atomic=True,

deepmd/infer/deep_wfc.py

@@ -35,14 +35,14 @@ def output_tensor_name(self) -> str:
     @property
     def output_def(self) -> ModelOutputDef:
         """Get the output definition of this model."""
-        # no reduciable or differentiable output is defined
+        # no reducible or differentiable output is defined
         return ModelOutputDef(
             FittingOutputDef(
                 [
                     OutputVariableDef(
                         self.output_tensor_name,
                         shape=[-1],
-                        reduciable=False,
+                        reducible=False,
                         r_differentiable=False,
                         c_differentiable=False,
                         atomic=True,

deepmd/pt/model/atomic_model/base_atomic_model.py

@@ -176,7 +176,7 @@ def atomic_output_def(self) -> FittingOutputDef:
                 OutputVariableDef(
                     name="mask",
                     shape=[1],
-                    reduciable=False,
+                    reducible=False,
                     r_differentiable=False,
                     c_differentiable=False,
                 )

deepmd/pt/model/atomic_model/linear_atomic_model.py

@@ -293,7 +293,7 @@ def fitting_output_def(self) -> FittingOutputDef:
                 OutputVariableDef(
                     name="energy",
                     shape=[1],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=True,
                     c_differentiable=True,
                 )

deepmd/pt/model/atomic_model/pairtab_atomic_model.py

@@ -125,7 +125,7 @@ def fitting_output_def(self) -> FittingOutputDef:
                 OutputVariableDef(
                     name="energy",
                     shape=[1],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=True,
                     c_differentiable=True,
                 )

deepmd/pt/model/model/transform_output.py

@@ -157,7 +157,7 @@ def fit_output_to_model_output(
         vdef = fit_output_def[kk]
         shap = vdef.shape
         atom_axis = -(len(shap) + 1)
-        if vdef.reduciable:
+        if vdef.reducible:
             kk_redu = get_reduce_name(kk)
             model_ret[kk_redu] = torch.sum(vv.to(redu_prec), dim=atom_axis)
             if vdef.r_differentiable:
@@ -196,7 +196,7 @@ def communicate_extended_output(
         vv = model_ret[kk]
         vdef = model_output_def[kk]
         new_ret[kk] = vv
-        if vdef.reduciable:
+        if vdef.reducible:
             kk_redu = get_reduce_name(kk)
             new_ret[kk_redu] = model_ret[kk_redu]
             # nf x nloc

deepmd/pt/model/task/denoise.py

@@ -77,14 +77,14 @@ def output_def(self):
                 OutputVariableDef(
                     "updated_coord",
                     [3],
-                    reduciable=False,
+                    reducible=False,
                     r_differentiable=False,
                     c_differentiable=False,
                 ),
                 OutputVariableDef(
                     "logits",
                     [-1],
-                    reduciable=False,
+                    reducible=False,
                     r_differentiable=False,
                     c_differentiable=False,
                 ),

deepmd/pt/model/task/dipole.py

@@ -66,10 +66,10 @@ class DipoleFittingNet(GeneralFitting):
         Random seed.
     r_differentiable
         If the variable is differentiated with respect to coordinates of atoms.
-        Only reduciable variable are differentiable.
+        Only reducible variable are differentiable.
     c_differentiable
         If the variable is differentiated with respect to the cell tensor (pbc case).
-        Only reduciable variable are differentiable.
+        Only reducible variable are differentiable.
     type_map: List[str], Optional
         A list of strings. Give the name to each type of atoms.
     """
@@ -142,7 +142,7 @@ def output_def(self) -> FittingOutputDef:
                 OutputVariableDef(
                     self.var_name,
                     [3],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=self.r_differentiable,
                     c_differentiable=self.c_differentiable,
                 ),

deepmd/pt/model/task/dos.py

@@ -91,7 +91,7 @@ def output_def(self) -> FittingOutputDef:
                 OutputVariableDef(
                     self.var_name,
                     [self.dim_out],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=False,
                     c_differentiable=False,
                 ),

deepmd/pt/model/task/ener.py

@@ -164,14 +164,14 @@ def output_def(self):
                 OutputVariableDef(
                     "energy",
                     [1],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=False,
                     c_differentiable=False,
                 ),
                 OutputVariableDef(
                     "dforce",
                     [3],
-                    reduciable=False,
+                    reducible=False,
                     r_differentiable=False,
                     c_differentiable=False,
                 ),

deepmd/pt/model/task/invar_fitting.py

@@ -149,7 +149,7 @@ def output_def(self) -> FittingOutputDef:
                 OutputVariableDef(
                     self.var_name,
                     [self.dim_out],
-                    reduciable=True,
+                    reducible=True,
                     r_differentiable=True,
                     c_differentiable=True,
                 ),