Merge branch 'devel' into 1108_default_fparam_stat

Author: Chengqian-Zhang

.devcontainer/build_cxx.sh

@@ -13,7 +13,7 @@ cmake -D ENABLE_TENSORFLOW=ON \
 	-D ENABLE_PYTORCH=ON \
 	-D ENABLE_PADDLE=ON \
 	-D CMAKE_INSTALL_PREFIX=${SCRIPT_PATH}/../dp/ \
-	-D LAMMPS_VERSION=stable_22Jul2025_update1 \
+	-D LAMMPS_VERSION=stable_22Jul2025_update2 \
 	-D CMAKE_BUILD_TYPE=Debug \
 	-D BUILD_TESTING:BOOL=TRUE \
 	-D TENSORFLOW_ROOT=${TENSORFLOW_ROOT} \

.pre-commit-config.yaml

@@ -29,7 +29,7 @@ repos:
         exclude: ^source/3rdparty
   - repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: v0.14.3
+    rev: v0.14.5
     hooks:
       - id: ruff
         args: ["--fix"]
@@ -60,7 +60,7 @@ repos:
       - id: blacken-docs
   # C++
   - repo: https://github.com/pre-commit/mirrors-clang-format
-    rev: v21.1.2
+    rev: v21.1.5
     hooks:
       - id: clang-format
         exclude: ^(source/3rdparty|source/lib/src/gpu/cudart/.+\.inc|.+\.ipynb$|.+\.json$)
@@ -154,7 +154,7 @@ repos:
         exclude: .pre-commit-config.yaml|source/lmp
   # customized pylint rules
   - repo: https://github.com/pylint-dev/pylint/
-    rev: v4.0.2
+    rev: v4.0.3
     hooks:
       - id: pylint
         entry: env PYTHONPATH=source/checker pylint

deepmd/pt/infer/deep_eval.py

@@ -397,9 +397,9 @@ def _get_request_defs(self, atomic: bool) -> list[OutputVariableDef]:
             The requested output definitions.
         """
         if atomic:
-            return list(self.output_def.var_defs.values())
+            output_defs = list(self.output_def.var_defs.values())
         else:
-            return [
+            output_defs = [
                 x
                 for x in self.output_def.var_defs.values()
                 if x.category
@@ -411,6 +411,13 @@ def _get_request_defs(self, atomic: bool) -> list[OutputVariableDef]:
                     OutputVariableCategory.DERV_R_DERV_R,
                 )
             ]
+        if not self.get_has_hessian():
+            output_defs = [
+                x
+                for x in output_defs
+                if x.category != OutputVariableCategory.DERV_R_DERV_R
+            ]
+        return output_defs
 
     def _eval_func(self, inner_func: Callable, numb_test: int, natoms: int) -> Callable:
         """Wrapper method with auto batch size.

deepmd/pt/utils/tabulate.py

@@ -46,7 +46,8 @@ class DPTabulate(BaseTabulate):
             The excluded pairs of types which have no interaction with each other.
             For example, `[[0, 1]]` means no interaction between type 0 and type 1.
     activation_function
-            The activation function in the embedding net. Supported options are {"tanh","gelu"} in common.ActivationFn.
+            The activation function in the embedding net. See :class:`ActivationFn`
+            for supported options (e.g. "tanh", "gelu", "relu", "silu").
     """
 
     def __init__(
@@ -84,6 +85,7 @@ def __init__(
             "relu6": 4,
             "softplus": 5,
             "sigmoid": 6,
+            "silu": 7,
         }
 
         activation = activation_fn.activation
@@ -468,6 +470,11 @@ def grad(xbar: torch.Tensor, y: torch.Tensor, functype: int) -> torch.Tensor:
     elif functype == 6:
         return y * (1 - y)
 
+    elif functype == 7:
+        # silu'(x) = sigmoid(x) * (1 + x * (1 - sigmoid(x)))
+        sig = torch.sigmoid(xbar)
+        return sig + xbar * sig * (1 - sig)
+
     else:
         raise ValueError(f"Unsupported function type: {functype}")
 
@@ -495,6 +502,12 @@ def grad_grad(xbar: torch.Tensor, y: torch.Tensor, functype: int) -> torch.Tenso
     elif functype == 6:
         return y * (1 - y) * (1 - 2 * y)
 
+    elif functype == 7:
+        sig = torch.sigmoid(xbar)
+        d_sig = sig * (1 - sig)
+        # silu''(x) = 2 * d_sig + x * d_sig * (1 - 2 * sig)
+        return 2 * d_sig + xbar * d_sig * (1 - 2 * sig)
+
     else:
         return -torch.ones_like(xbar)
 

deepmd/utils/data.py

@@ -14,6 +14,7 @@
 from typing import (
     Any,
     Optional,
+    Union,
 )
 
 import numpy as np
@@ -103,13 +104,10 @@ def __init__(
                     f"Elements {missing_elements} are not present in the provided `type_map`."
                 )
             if not self.mixed_type:
-                # Use vectorized operation for better performance with large atom counts
-                # Create a mapping array where old_type_idx -> new_type_idx
-                max_old_type = max(self.atom_type) + 1
-                type_mapping = np.zeros(max_old_type, dtype=np.int32)
-                for old_idx in range(len(self.type_map)):
-                    type_mapping[old_idx] = type_map.index(self.type_map[old_idx])
-                self.atom_type = type_mapping[self.atom_type].astype(np.int32)
+                old_to_new_type_idx = np.array(
+                    [type_map.index(name) for name in self.type_map], dtype=np.int32
+                )
+                self.atom_type = old_to_new_type_idx[self.atom_type].astype(np.int32)
             else:
                 self.enforce_type_map = True
                 sorter = np.argsort(type_map)
@@ -138,8 +136,7 @@ def __init__(
         self.shuffle_test = shuffle_test
         # set modifier
         self.modifier = modifier
-        # calculate prefix sum for get_item method
-        frames_list = [self._get_nframes(item) for item in self.dirs]
+        frames_list = [self._get_nframes(set_name) for set_name in self.dirs]
         self.nframes = np.sum(frames_list)
         # The prefix sum stores the range of indices contained in each directory, which is needed by get_item method
         self.prefix_sum = np.cumsum(frames_list).tolist()
@@ -341,8 +338,10 @@ def get_numb_set(self) -> int:
 
     def get_numb_batch(self, batch_size: int, set_idx: int) -> int:
         """Get the number of batches in a set."""
-        data = self._load_set(self.dirs[set_idx])
-        ret = data["coord"].shape[0] // batch_size
+        set_name = self.dirs[set_idx]
+        # Directly obtain the number of frames to avoid loading the entire dataset
+        nframes = self._get_nframes(set_name)
+        ret = nframes // batch_size
         if ret == 0:
             ret = 1
         return ret
@@ -581,18 +580,27 @@ def _shuffle_data(self, data: dict[str, Any]) -> dict[str, Any]:
                 ret[kk] = data[kk]
         return ret, idx
 
-    def _get_nframes(self, set_name: DPPath) -> int:
-        # get nframes
+    def _get_nframes(self, set_name: Union[DPPath, str]) -> int:
         if not isinstance(set_name, DPPath):
             set_name = DPPath(set_name)
         path = set_name / "coord.npy"
-        if self.data_dict["coord"]["high_prec"]:
-            coord = path.load_numpy().astype(GLOBAL_ENER_FLOAT_PRECISION)
+        if isinstance(set_name, DPH5Path):
+            nframes = path.root[path._name].shape[0]
         else:
-            coord = path.load_numpy().astype(GLOBAL_NP_FLOAT_PRECISION)
-        if coord.ndim == 1:
-            coord = coord.reshape([1, -1])
-        nframes = coord.shape[0]
+            # Read only the header to get shape
+            with open(str(path), "rb") as f:
+                version = np.lib.format.read_magic(f)
+                if version[0] == 1:
+                    shape, _fortran_order, _dtype = np.lib.format.read_array_header_1_0(
+                        f
+                    )
+                elif version[0] in [2, 3]:
+                    shape, _fortran_order, _dtype = np.lib.format.read_array_header_2_0(
+                        f
+                    )
+                else:
+                    raise ValueError(f"Unsupported .npy file version: {version}")
+            nframes = shape[0] if len(shape) > 1 else 1
         return nframes
 
     def reformat_data_torch(self, data: dict[str, Any]) -> dict[str, Any]:

doc/install/install-lammps.md

@@ -17,11 +17,11 @@ DeePMD-kit will generate a module called `USER-DEEPMD` in the `build` directory,
 
 ```bash
 cd /some/workspace
-wget https://github.com/lammps/lammps/archive/stable_22Jul2025_update1.tar.gz
-tar xf stable_22Jul2025_update1.tar.gz
+wget https://github.com/lammps/lammps/archive/stable_22Jul2025_update2.tar.gz
+tar xf stable_22Jul2025_update2.tar.gz
 ```
 
-The source code of LAMMPS is stored in the directory `lammps-stable_22Jul2025_update1`.
+The source code of LAMMPS is stored in the directory `lammps-stable_22Jul2025_update2`.
 
 Then, you can [build LAMMPS](https://docs.lammps.org/Build.html) with either make or CMake.
 
@@ -30,7 +30,7 @@ Then, you can [build LAMMPS](https://docs.lammps.org/Build.html) with either mak
 Now go into the LAMMPS code and copy the DeePMD-kit module like this
 
 ```bash
-cd lammps-stable_22Jul2025_update1/src/
+cd lammps-stable_22Jul2025_update2/src/
 cp -r $deepmd_source_dir/source/build/USER-DEEPMD .
 make yes-kspace
 make yes-extra-fix
@@ -60,8 +60,8 @@ make no-user-deepmd
 Now go into the LAMMPS directory and create a directory called `build`:
 
 ```bash
-mkdir -p lammps-stable_22Jul2025_update1/build/
-cd lammps-stable_22Jul2025_update1/build/
+mkdir -p lammps-stable_22Jul2025_update2/build/
+cd lammps-stable_22Jul2025_update2/build/
 ```
 
 Patch the LAMMPS `CMakeLists.txt` file:
@@ -94,15 +94,15 @@ Now download the LAMMPS code (`8Apr2021` or later), and uncompress it:
 
 ```bash
 cd /some/workspace
-wget https://github.com/lammps/lammps/archive/stable_22Jul2025_update1.tar.gz
-tar xf stable_22Jul2025_update1.tar.gz
+wget https://github.com/lammps/lammps/archive/stable_22Jul2025_update2.tar.gz
+tar xf stable_22Jul2025_update2.tar.gz
 ```
 
-The source code of LAMMPS is stored in the directory `lammps-stable_22Jul2025_update1`. The directory of the source code should be specified as the CMAKE argument `LAMMPS_SOURCE_ROOT` during installation of the DeePMD-kit C++ interface. Now go into the LAMMPS directory and create a directory called `build`
+The source code of LAMMPS is stored in the directory `lammps-stable_22Jul2025_update2`. The directory of the source code should be specified as the CMAKE argument `LAMMPS_SOURCE_ROOT` during installation of the DeePMD-kit C++ interface. Now go into the LAMMPS directory and create a directory called `build`
 
 ```bash
-mkdir -p lammps-stable_22Jul2025_update1/build/
-cd lammps-stable_22Jul2025_update1/build/
+mkdir -p lammps-stable_22Jul2025_update2/build/
+cd lammps-stable_22Jul2025_update2/build/
 ```
 
 Now build LAMMPS. Note that `PLUGIN` must be enabled, and `BUILD_SHARED_LIBS` must be set to `yes`. You can install any other package you want.

pyproject.toml

@@ -108,7 +108,7 @@ docs = [
     "sphinx-remove-toctrees",
 ]
 lmp = [
-    "lammps[mpi]~=2025.7.22.1.0",
+    "lammps[mpi]~=2025.7.22.2.0",
 ]
 ipi = [
     "ipi",
@@ -242,7 +242,7 @@ repair-wheel-command = """delocate-wheel --require-archs {delocate_archs} -w {de
 
 [tool.cibuildwheel.macos.environment]
 PIP_PREFER_BINARY = "1"
-DP_LAMMPS_VERSION = "stable_22Jul2025_update1"
+DP_LAMMPS_VERSION = "stable_22Jul2025_update2"
 DP_ENABLE_IPI = "1"
 DP_ENABLE_PYTORCH = "1"
 DP_ENABLE_PADDLE = "1"
@@ -278,7 +278,7 @@ before-build = [
 ]
 [tool.cibuildwheel.linux.environment]
 PIP_PREFER_BINARY = "1"
-DP_LAMMPS_VERSION = "stable_22Jul2025_update1"
+DP_LAMMPS_VERSION = "stable_22Jul2025_update2"
 DP_ENABLE_IPI = "1"
 DP_ENABLE_PYTORCH = "1"
 DP_ENABLE_PADDLE = "1"

source/install/build_cc.sh

@@ -26,7 +26,7 @@ cmake -D ENABLE_TENSORFLOW=ON \
 	-D USE_TF_PYTHON_LIBS=TRUE \
 	-D USE_PT_PYTHON_LIBS=TRUE \
 	${CUDA_ARGS} \
-	-D LAMMPS_VERSION=stable_22Jul2025_update1 \
+	-D LAMMPS_VERSION=stable_22Jul2025_update2 \
 	..
 cmake --build . -j${NPROC}
 cmake --install .

source/install/build_from_c.sh

@@ -13,7 +13,7 @@ NPROC=$(nproc --all)
 BUILD_TMP_DIR=${SCRIPT_PATH}/../build
 mkdir -p ${BUILD_TMP_DIR}
 cd ${BUILD_TMP_DIR}
-cmake -DCMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} -DDEEPMD_C_ROOT=${DEEPMD_C_ROOT} -DLAMMPS_VERSION=stable_22Jul2025_update1 ..
+cmake -DCMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} -DDEEPMD_C_ROOT=${DEEPMD_C_ROOT} -DLAMMPS_VERSION=stable_22Jul2025_update2 ..
 cmake --build . -j${NPROC}
 cmake --install .
 cmake --build . --target=lammps

source/install/build_lammps.sh

@@ -14,7 +14,7 @@ BUILD_TMP_DIR=${SCRIPT_PATH}/../build_lammps
 mkdir -p ${BUILD_TMP_DIR}
 cd ${BUILD_TMP_DIR}
 # download LAMMMPS
-LAMMPS_VERSION=stable_22Jul2025_update1
+LAMMPS_VERSION=stable_22Jul2025_update2
 if [ ! -d "lammps-${LAMMPS_VERSION}" ]; then
 	curl -L -o lammps.tar.gz https://github.com/lammps/lammps/archive/refs/tags/${LAMMPS_VERSION}.tar.gz
 	tar vxzf lammps.tar.gz