Merge pull request #1217 from amcadmus/master

Merge recent updates on devel to master.

Author: amcadmus

.readthedocs.yml

@@ -1,3 +1,4 @@
 version: 2
 conda:
-  environment: doc/environment.yml
+  environment: doc/environment.yml
+formats: all

deepmd/descriptor/hybrid.py

@@ -26,15 +26,17 @@ class DescrptHybrid (Descriptor):
 
     Parameters
     ----------
-    descrpt_list : list
+    list : list
             Build a descriptor from the concatenation of the list of descriptors.
     """
     def __init__ (self, 
-                  descrpt_list : list
+                  list : list
     ) -> None :
         """
         Constructor
         """
+        # warning: list is conflict with built-in list
+        descrpt_list = list
         if descrpt_list == [] or descrpt_list is None:
             raise RuntimeError('cannot build descriptor from an empty list of descriptors.')
         formatted_descript_list = []

deepmd/descriptor/se_a.py

@@ -3,7 +3,7 @@
 from typing import Tuple, List, Dict, Any
 
 from deepmd.env import tf
-from deepmd.common import get_activation_func, get_precision, ACTIVATION_FN_DICT, PRECISION_DICT, docstring_parameter, get_np_precision
+from deepmd.common import get_activation_func, get_precision, ACTIVATION_FN_DICT, PRECISION_DICT, docstring_parameter
 from deepmd.utils.argcheck import list_to_doc
 from deepmd.env import GLOBAL_TF_FLOAT_PRECISION
 from deepmd.env import GLOBAL_NP_FLOAT_PRECISION
@@ -13,7 +13,7 @@
 from deepmd.utils.tabulate import DPTabulate
 from deepmd.utils.type_embed import embed_atom_type
 from deepmd.utils.sess import run_sess
-from deepmd.utils.graph import load_graph_def, get_tensor_by_name_from_graph, get_embedding_net_variables
+from deepmd.utils.graph import load_graph_def, get_tensor_by_name_from_graph
 from .descriptor import Descriptor
 from .se import DescrptSe
 
@@ -133,7 +133,6 @@ def __init__ (self,
         self.compress_activation_fn = get_activation_func(activation_function)
         self.filter_activation_fn = get_activation_func(activation_function)
         self.filter_precision = get_precision(precision)
-        self.filter_np_precision = get_np_precision(precision)
         self.exclude_types = set()
         for tt in exclude_types:
             assert(len(tt) == 2)
@@ -687,7 +686,7 @@ def _filter_lower(
             net = 'filter_-1_net_' + str(type_i)
           else:
             net = 'filter_' + str(type_input) + '_net_' + str(type_i)
-          return op_module.tabulate_fusion(self.table.data[net].astype(self.filter_np_precision), info, xyz_scatter, tf.reshape(inputs_i, [natom, shape_i[1]//4, 4]), last_layer_size = outputs_size[-1])  
+          return op_module.tabulate_fusion(tf.cast(self.table.data[net], self.filter_precision), info, xyz_scatter, tf.reshape(inputs_i, [natom, shape_i[1]//4, 4]), last_layer_size = outputs_size[-1])  
         else:
           if (not is_exclude):
               xyz_scatter = embedding_net(

deepmd/utils/argcheck.py

@@ -478,6 +478,8 @@ def loss_ener():
     doc_limit_pref_v = limit_pref('virial')
     doc_start_pref_ae = start_pref('atom_ener')
     doc_limit_pref_ae = limit_pref('atom_ener')
+    doc_start_pref_pf = start_pref('atom_pref')
+    doc_limit_pref_pf = limit_pref('atom_pref')
     doc_relative_f = 'If provided, relative force error will be used in the loss. The difference of force will be normalized by the magnitude of the force in the label with a shift given by `relative_f`, i.e. DF_i / ( || F || + relative_f ) with DF denoting the difference between prediction and label and || F || denoting the L2 norm of the label.'
     return [
         Argument("start_pref_e", [float,int], optional = True, default = 0.02, doc = doc_start_pref_e),
@@ -488,6 +490,8 @@ def loss_ener():
         Argument("limit_pref_v", [float,int], optional = True, default = 0.00, doc = doc_limit_pref_v),
         Argument("start_pref_ae", [float,int], optional = True, default = 0.00, doc = doc_start_pref_ae),
         Argument("limit_pref_ae", [float,int], optional = True, default = 0.00, doc = doc_limit_pref_ae),
+        Argument("start_pref_pf", [float,int], optional = True, default = 0.00, doc = doc_start_pref_pf),
+        Argument("limit_pref_pf", [float,int], optional = True, default = 0.00, doc = doc_limit_pref_pf),
         Argument("relative_f", [float,None], optional = True, doc = doc_relative_f)
     ]
 

doc/install/install-from-source.md

@@ -174,7 +174,7 @@ One may add the following arguments to `cmake`:
 | -DCUDA_TOOLKIT_ROOT_DIR=<value> | Path         | Detected automatically | The path to the CUDA toolkit directory. |
 | -DUSE_ROCM_TOOLKIT=<value> | `TRUE` or `FALSE` | `FALSE`       | If `TRUE`, Build GPU support with ROCM toolkit. |
 | -DROCM_ROOT=<value> | Path         | Detected automatically | The path to the ROCM toolkit directory. |
-| -DLAMMPS_VERSION_NUMBER=<value> | Number         | `20201029` | Only neccessary for LAMMPS built-in mode. The version number of LAMMPS (yyyymmdd). |
+| -DLAMMPS_VERSION_NUMBER=<value> | Number         | `20210929` | Only neccessary for LAMMPS built-in mode. The version number of LAMMPS (yyyymmdd). |
 | -DLAMMPS_SOURCE_ROOT=<value> | Path         | - | Only neccessary for LAMMPS plugin mode. The path to the LAMMPS source code (later than 8Apr2021). If not assigned, the plugin mode will not be enabled. |
 
 If the cmake has executed successfully, then 

doc/install/install-lammps.md

@@ -12,12 +12,12 @@ make lammps
 DeePMD-kit will generate a module called `USER-DEEPMD` in the `build` directory. If you need low precision version, move `env_low.sh` to `env.sh` in the directory. Now download the LAMMPS code (`29Oct2020` or later), and uncompress it:
 ```bash
 cd /some/workspace
-wget https://github.com/lammps/lammps/archive/stable_29Oct2020.tar.gz
-tar xf stable_29Oct2020.tar.gz
+wget https://github.com/lammps/lammps/archive/stable_29Sep2021.tar.gz
+tar xf stable_29Sep2021.tar.gz
 ```
-The source code of LAMMPS is stored in directory `lammps-stable_29Oct2020`. Now go into the LAMMPS code and copy the DeePMD-kit module like this
+The source code of LAMMPS is stored in directory `lammps-stable_29Sep2021`. Now go into the LAMMPS code and copy the DeePMD-kit module like this
 ```bash
-cd lammps-stable_29Oct2020/src/
+cd lammps-stable_29Sep2021/src/
 cp -r $deepmd_source_dir/source/build/USER-DEEPMD .
 ```
 Now build LAMMPS
@@ -43,22 +43,22 @@ Starting from `8Apr2021`, LAMMPS also provides a plugin mode, allowing one build
 Now download the LAMMPS code (`8Apr2021` or later), and uncompress it:
 ```bash
 cd /some/workspace
-wget https://github.com/lammps/lammps/archive/patch_30Jul2021.tar.gz
-tar xf patch_30Jul2021.tar.gz
+wget https://github.com/lammps/lammps/archive/stable_29Sep2021.tar.gz
+tar xf stable_29Sep2021.tar.gz
 ```
-The source code of LAMMPS is stored in directory `lammps-patch_30Jul2021`. Now go into the LAMMPS code and create a directory called `build`
+The source code of LAMMPS is stored in directory `lammps-stable_29Sep2021`. Now go into the LAMMPS code and create a directory called `build`
 ```bash
-mkdir -p lammps-patch_30Jul2021/build/
-cd lammps-patch_30Jul2021/build/
+mkdir -p lammps-stable_29Sep2021/build/
+cd lammps-stable_29Sep2021/build/
 ```
 Now build LAMMPS. Note that `PLUGIN` and `KSPACE` package must be enabled, and `BUILD_SHARED_LIBS` must be set to `yes`. You can install any other package you want.
 ```bash
-cmake -D PKG_PLUGIN=ON -D PKG_KSPACE=ON -D LAMMPS_INSTALL_RPATH=ON -D BUILD_SHARED_LIBS=yes -D CMAKE_INSTALL_PREFIX=${deepmd_root} ../cmake
+cmake -D PKG_PLUGIN=ON -D PKG_KSPACE=ON -D LAMMPS_INSTALL_RPATH=ON -D BUILD_SHARED_LIBS=yes -D CMAKE_INSTALL_PREFIX=${deepmd_root} -D CMAKE_INSTALL_LIBDIR=lib -D CMAKE_INSTALL_FULL_LIBDIR=${deepmd_root}/lib ../cmake
 make -j4
 make install
 ```
 
 If everything works fine, you will end up with an executable `${deepmd_root}/lmp`.
 ```bash
 ${deepmd_root}/lmp -h
-```
+```

doc/third-party/lammps-command.md

@@ -5,7 +5,7 @@
 If you are using the plugin mode, enable DeePMD-kit package in LAMMPS with `plugin` command:
 
 ```
-plugin load path/to/deepmd/lib/libdeepmd_lmp.so
+plugin load libdeepmd_lmp.so
 ```
 
 The built-in mode doesn't need this step.

examples/water/lmp/in.plugin.lammps

@@ -11,8 +11,8 @@ read_data	water.lmp
 mass 		1 16
 mass		2 2
 
-# load the plugin at <install_prefix>/lib/libdeepmd_lmp.so
-plugin load ../../../dp/lib/libdeepmd_lmp.so
+# load the deepmd plugin
+plugin load libdeepmd_lmp.so
 
 pair_style	deepmd frozen_model.pb
 pair_coeff  * *	

source/install/build_cc.sh

@@ -20,7 +20,7 @@ NPROC=$(nproc --all)
 BUILD_TMP_DIR=${SCRIPT_PATH}/../build
 mkdir -p ${BUILD_TMP_DIR}
 cd ${BUILD_TMP_DIR}
-cmake -DCMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} -DINSTALL_TENSORFLOW=TRUE ${CUDA_ARGS} -DLAMMPS_VERSION=patch_30Jul2021 -DUSE_TTM=TRUE ..
+cmake -DCMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} -DINSTALL_TENSORFLOW=TRUE ${CUDA_ARGS} -DLAMMPS_VERSION=stable_29Sep2021 -DUSE_TTM=TRUE ..
 make -j${NPROC}
 make install
 

source/install/build_lammps.sh

@@ -15,7 +15,7 @@ BUILD_TMP_DIR=${SCRIPT_PATH}/../build_lammps
 mkdir -p ${BUILD_TMP_DIR}
 cd ${BUILD_TMP_DIR}
 # download LAMMMPS
-LAMMPS_VERSION=patch_30Jul2021
+LAMMPS_VERSION=stable_29Sep2021
 if [ ! -d "lammps-${LAMMPS_VERSION}" ]
 then
 	curl -L -o lammps.tar.gz https://github.com/lammps/lammps/archive/refs/tags/${LAMMPS_VERSION}.tar.gz
@@ -25,7 +25,7 @@ fi
 cd ${BUILD_TMP_DIR}/lammps-${LAMMPS_VERSION}
 mkdir -p ${BUILD_TMP_DIR}/lammps-${LAMMPS_VERSION}/build
 cd ${BUILD_TMP_DIR}/lammps-${LAMMPS_VERSION}/build
-cmake -C ../cmake/presets/all_off.cmake -D PKG_PLUGIN=ON -D PKG_KSPACE=ON -D BUILD_SHARED_LIBS=yes -D LAMMPS_INSTALL_RPATH=ON -D CMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} ../cmake
+cmake -C ../cmake/presets/all_off.cmake -D PKG_PLUGIN=ON -D PKG_KSPACE=ON -D BUILD_SHARED_LIBS=yes -D LAMMPS_INSTALL_RPATH=ON -D CMAKE_INSTALL_PREFIX=${INSTALL_PREFIX} -D CMAKE_INSTALL_LIBDIR=lib -D CMAKE_INSTALL_FULL_LIBDIR=${INSTALL_PREFIX}/lib ../cmake
 
 make -j${NPROC}
 make install