feat(jax/array-api): hybrid descriptor

deepmd/dpmodel/descriptor/hybrid.py

@@ -6,6 +6,7 @@
     Union,
 )
 
+import array_api_compat
 import numpy as np
 
 from deepmd.dpmodel.common import (
@@ -66,7 +67,7 @@ def __init__(
             ), f"number of atom types in {ii}th descriptor {self.descrpt_list[0].__class__.__name__} does not match others"
         # if hybrid sel is larger than sub sel, the nlist needs to be cut for each type
         hybrid_sel = self.get_sel()
-        self.nlist_cut_idx: list[np.ndarray] = []
+        nlist_cut_idx: list[np.ndarray] = []
         if self.mixed_types() and not all(
             descrpt.mixed_types() for descrpt in self.descrpt_list
         ):
@@ -92,7 +93,8 @@ def __init__(
             cut_idx = np.concatenate(
                 [range(ss, ee) for ss, ee in zip(start_idx, end_idx)]
             )
-            self.nlist_cut_idx.append(cut_idx)
+            nlist_cut_idx.append(cut_idx)
+        self.nlist_cut_idx = nlist_cut_idx
 
     def get_rcut(self) -> float:
         """Returns the cut-off radius."""
@@ -242,6 +244,7 @@ def call(
         sw
             The smooth switch function.
         """
+        xp = array_api_compat.array_namespace(coord_ext, atype_ext, nlist)
         out_descriptor = []
         out_gr = []
         out_g2 = None
@@ -258,7 +261,7 @@ def call(
         for descrpt, nci in zip(self.descrpt_list, self.nlist_cut_idx):
             # cut the nlist to the correct length
             if self.mixed_types() == descrpt.mixed_types():
-                nl = nlist[:, :, nci]
+                nl = xp.take(nlist, nci, axis=2)
             else:
                 # mixed_types is True, but descrpt.mixed_types is False
                 assert nl_distinguish_types is not None
@@ -268,8 +271,8 @@ def call(
             if gr is not None:
                 out_gr.append(gr)
 
-        out_descriptor = np.concatenate(out_descriptor, axis=-1)
-        out_gr = np.concatenate(out_gr, axis=-2) if out_gr else None
+        out_descriptor = xp.concat(out_descriptor, axis=-1)
+        out_gr = xp.concat(out_gr, axis=-2) if out_gr else None
         return out_descriptor, out_gr, out_g2, out_h2, out_sw
 
     @classmethod

deepmd/jax/descriptor/__init__.py

@@ -2,6 +2,9 @@
 from deepmd.jax.descriptor.dpa1 import (
     DescrptDPA1,
 )
+from deepmd.jax.descriptor.hybrid import (
+    DescrptHybrid,
+)
 from deepmd.jax.descriptor.se_e2_a import (
     DescrptSeA,
 )
@@ -13,4 +16,5 @@
     "DescrptSeA",
     "DescrptSeR",
     "DescrptDPA1",
+    "DescrptHybrid",
 ]

deepmd/jax/descriptor/hybrid.py

@@ -0,0 +1,26 @@
+# SPDX-License-Identifier: LGPL-3.0-or-later
+from typing import (
+    Any,
+)
+
+from deepmd.dpmodel.descriptor.hybrid import DescrptHybrid as DescrptHybridDP
+from deepmd.jax.common import (
+    ArrayAPIVariable,
+    flax_module,
+    to_jax_array,
+)
+from deepmd.jax.descriptor.base_descriptor import (
+    BaseDescriptor,
+)
+
+
+@BaseDescriptor.register("hybrid")
+@flax_module
+class DescrptHybrid(DescrptHybridDP):
+    def __setattr__(self, name: str, value: Any) -> None:
+        if name in {"nlist_cut_idx"}:
+            value = [ArrayAPIVariable(to_jax_array(vv)) for vv in value]
+        elif name in {"descrpt_list"}:
+            value = [BaseDescriptor.deserialize(vv.serialize()) for vv in value]
+
+        return super().__setattr__(name, value)

doc/model/train-hybrid.md

@@ -1,7 +1,7 @@
-# Descriptor `"hybrid"` {{ tensorflow_icon }} {{ pytorch_icon }} {{ dpmodel_icon }}
+# Descriptor `"hybrid"` {{ tensorflow_icon }} {{ pytorch_icon }} {{ jax_icon }} {{ dpmodel_icon }}
 
 :::{note}
-**Supported backends**: TensorFlow {{ tensorflow_icon }}, PyTorch {{ pytorch_icon }}, DP {{ dpmodel_icon }}
+**Supported backends**: TensorFlow {{ tensorflow_icon }}, PyTorch {{ pytorch_icon }}, JAX {{ jax_icon }}, DP {{ dpmodel_icon }}
 :::
 
 This descriptor hybridizes multiple descriptors to form a new descriptor. For example, we have a list of descriptors denoted by $\mathcal D_1$, $\mathcal D_2$, ..., $\mathcal D_N$, the hybrid descriptor this the concatenation of the list, i.e. $\mathcal D = (\mathcal D_1, \mathcal D_2, \cdots, \mathcal D_N)$.

source/tests/array_api_strict/descriptor/__init__.py

@@ -1 +1,20 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
+from .dpa1 import (
+    DescrptDPA1,
+)
+from .hybrid import (
+    DescrptHybrid,
+)
+from .se_e2_a import (
+    DescrptSeA,
+)
+from .se_e2_r import (
+    DescrptSeR,
+)
+
+__all__ = [
+    "DescrptSeA",
+    "DescrptSeR",
+    "DescrptDPA1",
+    "DescrptHybrid",
+]

source/tests/array_api_strict/descriptor/base_descriptor.py

@@ -0,0 +1,11 @@
+# SPDX-License-Identifier: LGPL-3.0-or-later
+from typing import (
+    Any,
+)
+
+from deepmd.dpmodel.descriptor.make_base_descriptor import (
+    make_base_descriptor,
+)
+
+# no type annotations standard in array api
+BaseDescriptor = make_base_descriptor(Any)

source/tests/array_api_strict/descriptor/dpa1.py

@@ -27,6 +27,9 @@
 from ..utils.type_embed import (
     TypeEmbedNet,
 )
+from .base_descriptor import (
+    BaseDescriptor,
+)
 
 
 class GatedAttentionLayer(GatedAttentionLayerDP):
@@ -72,6 +75,8 @@ def __setattr__(self, name: str, value: Any) -> None:
         return super().__setattr__(name, value)
 
 
+@BaseDescriptor.register("dpa1")
+@BaseDescriptor.register("se_atten")
 class DescrptDPA1(DescrptDPA1DP):
     def __setattr__(self, name: str, value: Any) -> None:
         if name == "se_atten":

source/tests/array_api_strict/descriptor/hybrid.py

@@ -0,0 +1,24 @@
+# SPDX-License-Identifier: LGPL-3.0-or-later
+from typing import (
+    Any,
+)
+
+from deepmd.dpmodel.descriptor.hybrid import DescrptHybrid as DescrptHybridDP
+
+from ..common import (
+    to_array_api_strict_array,
+)
+from .base_descriptor import (
+    BaseDescriptor,
+)
+
+
+@BaseDescriptor.register("hybrid")
+class DescrptHybrid(DescrptHybridDP):
+    def __setattr__(self, name: str, value: Any) -> None:
+        if name in {"nlist_cut_idx"}:
+            value = [to_array_api_strict_array(vv) for vv in value]
+        elif name in {"descrpt_list"}:
+            value = [BaseDescriptor.deserialize(vv.serialize()) for vv in value]
+
+        return super().__setattr__(name, value)

source/tests/array_api_strict/descriptor/se_e2_a.py

@@ -14,8 +14,13 @@
 from ..utils.network import (
     NetworkCollection,
 )
+from .base_descriptor import (
+    BaseDescriptor,
+)
 
 
+@BaseDescriptor.register("se_e2_a")
+@BaseDescriptor.register("se_a")
 class DescrptSeA(DescrptSeADP):
     def __setattr__(self, name: str, value: Any) -> None:
         if name in {"dstd", "davg"}:

source/tests/array_api_strict/descriptor/se_e2_r.py

@@ -14,8 +14,13 @@
 from ..utils.network import (
     NetworkCollection,
 )
+from .base_descriptor import (
+    BaseDescriptor,
+)
 
 
+@BaseDescriptor.register("se_e2_r")
+@BaseDescriptor.register("se_r")
 class DescrptSeR(DescrptSeRDP):
     def __setattr__(self, name: str, value: Any) -> None:
         if name in {"dstd", "davg"}:

source/tests/consistent/descriptor/test_hybrid.py

@@ -12,6 +12,8 @@
 )
 
 from ..common import (
+    INSTALLED_ARRAY_API_STRICT,
+    INSTALLED_JAX,
     INSTALLED_PT,
     INSTALLED_TF,
     CommonTest,
@@ -28,6 +30,16 @@
     from deepmd.tf.descriptor.hybrid import DescrptHybrid as DescrptHybridTF
 else:
     DescrptHybridTF = None
+if INSTALLED_JAX:
+    from deepmd.jax.descriptor.hybrid import DescrptHybrid as DescrptHybridJAX
+else:
+    DescrptHybridJAX = None
+if INSTALLED_ARRAY_API_STRICT:
+    from ...array_api_strict.descriptor.hybrid import (
+        DescrptHybrid as DescrptHybridStrict,
+    )
+else:
+    DescrptHybridStrict = None
 from deepmd.utils.argcheck import (
     descrpt_hybrid_args,
 )
@@ -68,8 +80,13 @@ def data(self) -> dict:
     tf_class = DescrptHybridTF
     dp_class = DescrptHybridDP
     pt_class = DescrptHybridPT
+    jax_class = DescrptHybridJAX
+    array_api_strict_class = DescrptHybridStrict
     args = descrpt_hybrid_args()
 
+    skip_jax = not INSTALLED_JAX
+    skip_array_api_strict = not INSTALLED_ARRAY_API_STRICT
+
     def setUp(self):
         CommonTest.setUp(self)
 
@@ -132,5 +149,23 @@ def eval_pt(self, pt_obj: Any) -> Any:
             self.box,
         )
 
+    def eval_array_api_strict(self, array_api_strict_obj: Any) -> Any:
+        return self.eval_array_api_strict_descriptor(
+            array_api_strict_obj,
+            self.natoms,
+            self.coords,
+            self.atype,
+            self.box,
+        )
+
+    def eval_jax(self, jax_obj: Any) -> Any:
+        return self.eval_jax_descriptor(
+            jax_obj,
+            self.natoms,
+            self.coords,
+            self.atype,
+            self.box,
+        )
+
     def extract_ret(self, ret: Any, backend) -> tuple[np.ndarray, ...]:
         return (ret[0],)