Yaml configuration file support

README.md

@@ -10,9 +10,9 @@
  	- [Deep Potential in a nutshell](#deep-potential-in-a-nutshell)
 - [Download and install](#download-and-install)
     - [Easy installation methods](#easy-installation-methods)
+      - [Offline packages](#offline-packages)
       - [With Docker](#with-docker)
       - [With conda](#with-conda)
-      - [Offline packages](#offline-packages)
     - [Install the python interaction](#install-the-python-interface)
       - [Install the Tensorflow's python interface](#install-the-tensorflows-python-interface)
       - [Install the DeePMD-kit's python interface](#install-the-deepmd-kits-python-interface)
@@ -90,8 +90,10 @@ Please follow our [github](https://github.com/deepmodeling/deepmd-kit) webpage t
 ## Easy installation methods
 There various easy methods to install DeePMD-kit. Choose one that you prefer. If you want to build by yourself, jump to the next two sections.
 
-### With Docker
-A docker for installing the DeePMD-kit on CentOS 7 is available [here](https://github.com/frankhan91/deepmd-kit_docker).
+After your easy installation, DeePMD-kit (`dp`) and LAMMPS (`lmp`) will be available to execute. You can try `dp -h` and `lmp -h` to see the help. `mpirun` is also available considering you may want to run LAMMPS in parallel.
+
+### Offline packages
+Both CPU and GPU version offline packages are avaiable in [the Releases page](https://github.com/deepmodeling/deepmd-kit/releases).
 
 ### With conda
 DeePMD-kit is avaiable with [conda](https://github.com/conda/conda). Install [Anaconda](https://www.anaconda.com/distribution/#download-section) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html) first.
@@ -101,13 +103,23 @@ To install the CPU version:
 conda install deepmd-kit=*=*cpu lammps-dp=*=*cpu -c deepmodeling
 ```
 
-To install the GPU version containing [CUDA 10.0](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver):
+To install the GPU version containing [CUDA 10.1](https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility__table-toolkit-driver):
 ```bash
 conda install deepmd-kit=*=*gpu lammps-dp=*=*gpu -c deepmodeling
 ```
 
-### Offline packages
-Both CPU and GPU version offline package are avaiable in [the Releases page](https://github.com/deepmodeling/deepmd-kit/releases).
+### With Docker
+A docker for installing the DeePMD-kit is available [here](https://github.com/orgs/deepmodeling/packages/container/deepmd-kit).
+
+To pull the CPU version:
+```bash
+docker pull ghcr.io/deepmodeling/deepmd-kit:1.2.0_cpu
+```
+
+To pull the GPU version:
+```bash
+docker pull ghcr.io/deepmodeling/deepmd-kit:1.2.0_cuda10.1_gpu
+```
 
 ## Install the python interface 
 ### Install the Tensorflow's python interface

data/json/json2yaml.py

@@ -0,0 +1,37 @@
+#!/usr/bin/env python3
+
+import argparse
+import json
+from pathlib import Path
+from warnings import warn
+
+import yaml
+
+
+def _main():
+    parser = argparse.ArgumentParser(
+        description="convert json config file to yaml",
+        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+
+    # get all json files in dir
+    jsons = [p for p in Path.cwd().glob("*.json")]
+    # use the newest as autosuggestion
+    jsons.sort(key=lambda x: x.stat().st_mtime, reverse=True)
+    jfile = jsons[0]
+    yfile = jfile.with_suffix(".yaml")
+
+    parser.add_argument("INPUT", default=jfile, type=Path, nargs="?",
+                        help="input json file")
+    parser.add_argument("OUTPUT", default=yfile, type=Path, nargs="?",
+                        help="output yaml file")
+    args = parser.parse_args()
+
+    with args.INPUT.open("r") as infile, args.OUTPUT.open("w") as outfile:
+        yaml.dump(json.load(infile), outfile, default_flow_style=False,
+                  sort_keys=False)
+
+    warn("The order of the keys won't be preserved!", SyntaxWarning)
+    warn("_comment keys will also be lostt in the conversion")
+
+if __name__ == "__main__":
+    _main()

setup.py

@@ -4,18 +4,8 @@
 from setuptools_scm import get_version
 from packaging.version import LegacyVersion
 from os import path, makedirs
-import imp, sys, platform
+import os, imp, sys, platform, sysconfig
 
-def get_dp_install_path() :
-    site_packages_path = path.join(path.dirname(path.__file__), 'site-packages')
-    dp_scm_version     = get_version(root="./", relative_to=__file__)
-    python_version     = 'py' + str(sys.version_info.major + sys.version_info.minor * 0.1)
-    os_info            = sys.platform
-    machine_info       = platform.machine()
-    dp_pip_install_path    = site_packages_path + '/deepmd'
-    dp_setup_install_path    = site_packages_path + '/deepmd_kit-' + dp_scm_version + '-' + python_version + '-' + os_info + '-' + machine_info + '.egg/deepmd'
-
-    return dp_pip_install_path, dp_setup_install_path
 
 readme_file = path.join(path.dirname(path.abspath(__file__)), 'README.md')
 try:
@@ -31,7 +21,8 @@ def get_dp_install_path() :
     site_packages_path = path.join(path.dirname(path.__file__), 'site-packages')
     tf_install_dir = imp.find_module('tensorflow', [site_packages_path])[1]
 
-install_requires=['numpy', 'scipy']
+
+install_requires=['numpy', 'scipy', 'pyyaml']
 setup_requires=['setuptools_scm', 'scikit-build', 'cmake']
 
 # add cmake as a build requirement if cmake>3.0 is not installed
@@ -46,7 +37,6 @@ def get_dp_install_path() :
 except OSError:
     pass
 
-dp_pip_install_path, dp_setup_install_path = get_dp_install_path()
 
 setup(
     name="deepmd-kit",
@@ -70,8 +60,6 @@ def get_dp_install_path() :
                 '-DBUILD_PY_IF:BOOL=TRUE', 
                 '-DBUILD_CPP_IF:BOOL=FALSE',
                 '-DFLOAT_PREC:STRING=high',
-                '-DDP_PIP_INSTALL_PATH=%s' % dp_pip_install_path,
-                '-DDP_SETUP_INSTALL_PATH=%s' % dp_setup_install_path,
     ],
     cmake_source_dir='source',
     cmake_minimum_required_version='3.0',

source/op/CMakeLists.txt

@@ -25,7 +25,7 @@ endif (BUILD_CPP_IF)
 
 if (BUILD_PY_IF)
   set(CMAKE_BUILD_WITH_INSTALL_RPATH TRUE)
-  set(CMAKE_INSTALL_RPATH DESTINATION ${DP_PIP_INSTALL_PATH} ${DP_SETUP_INSTALL_PATH} ${CMAKE_BINARY_DIR}/op/cuda)
+  set(CMAKE_INSTALL_RPATH $ORIGIN)
   if (USE_CUDA_TOOLKIT)
     add_library(op_abi SHARED ${OP_PY_CUDA_SRC} ${OP_LIB})
     add_library(op_grads SHARED ${OP_GRADS_SRC})

source/op/cuda/descrpt_se_a.cu

@@ -77,19 +77,20 @@ __device__ inline T dev_dot(T * arr1, T * arr2) {
     return arr1[0] * arr2[0] + arr1[1] * arr2[1] + arr1[2] * arr2[2];
 }
 
-__device__ inline void spline5_switch(compute_t & vv,
-        compute_t & dd,
-        compute_t & xx, 
-		const compute_t & rmin, 
-		const compute_t & rmax) 
+template<typename FPTYPE>
+__device__ inline void spline5_switch(FPTYPE & vv,
+        FPTYPE & dd,
+        FPTYPE & xx, 
+		const float & rmin, 
+		const float & rmax) 
 {
     if (xx < rmin) {
         dd = 0;
         vv = 1;
     }
     else if (xx < rmax) {
-        compute_t uu = (xx - rmin) / (rmax - rmin) ;
-        compute_t du = 1. / (rmax - rmin) ;
+        FPTYPE uu = (xx - rmin) / (rmax - rmin) ;
+        FPTYPE du = 1. / (rmax - rmin) ;
         vv = uu*uu*uu * (-6 * uu*uu + 15 * uu - 10) + 1;
         dd = ( 3 * uu*uu * (-6 * uu*uu + 15 * uu - 10) + uu*uu*uu * (-12 * uu + 15) ) * du;
     }
@@ -180,20 +181,21 @@ __global__ void format_nlist_fill_b_se_a(int * nlist,
 }
 //it's ok!
 
-__global__ void compute_descriptor_se_a (VALUETYPE* descript,
+template<typename FPTYPE>
+__global__ void compute_descriptor_se_a (FPTYPE* descript,
                             const int ndescrpt,
-                            VALUETYPE* descript_deriv,
+                            FPTYPE* descript_deriv,
                             const int descript_deriv_size,
-                            VALUETYPE* rij,
+                            FPTYPE* rij,
                             const int rij_size,
                             const int* type,
-                            const VALUETYPE* avg,
-                            const VALUETYPE* std,
+                            const FPTYPE* avg,
+                            const FPTYPE* std,
                             int* nlist,
                             const int nlist_size,
-                            const VALUETYPE* coord,
-                            const VALUETYPE rmin,
-                            const VALUETYPE rmax,
+                            const FPTYPE* coord,
+                            const float rmin,
+                            const float rmax,
                             const int sec_a_size)
 {   
     // <<<nloc, sec_a.back()>>>
@@ -204,24 +206,24 @@ __global__ void compute_descriptor_se_a (VALUETYPE* descript,
     if (idy >= sec_a_size) {return;}
 
     // else {return;}
-    VALUETYPE * row_descript = descript + idx * ndescrpt;
-    VALUETYPE * row_descript_deriv = descript_deriv + idx * descript_deriv_size;
-    VALUETYPE * row_rij = rij + idx * rij_size;
+    FPTYPE * row_descript = descript + idx * ndescrpt;
+    FPTYPE * row_descript_deriv = descript_deriv + idx * descript_deriv_size;
+    FPTYPE * row_rij = rij + idx * rij_size;
     int * row_nlist = nlist + idx * nlist_size;
 
     if (row_nlist[idy] >= 0) {
         const int & j_idx = row_nlist[idy];
         for (int kk = 0; kk < 3; kk++) {
             row_rij[idy * 3 + kk] = coord[j_idx * 3 + kk] - coord[idx * 3 + kk];
         }
-        const compute_t * rr = &row_rij[idy * 3 + 0];
-        compute_t nr2 = dev_dot(rr, rr);
-        compute_t inr = 1./sqrt(nr2);
-        compute_t nr = nr2 * inr;
-        compute_t inr2 = inr * inr;
-        compute_t inr4 = inr2 * inr2;
-        compute_t inr3 = inr4 * nr;
-        compute_t sw, dsw;
+        const FPTYPE * rr = &row_rij[idy * 3 + 0];
+        FPTYPE nr2 = dev_dot(rr, rr);
+        FPTYPE inr = 1./sqrt(nr2);
+        FPTYPE nr = nr2 * inr;
+        FPTYPE inr2 = inr * inr;
+        FPTYPE inr4 = inr2 * inr2;
+        FPTYPE inr3 = inr4 * nr;
+        FPTYPE sw, dsw;
         spline5_switch(sw, dsw, nr, rmin, rmax);
         row_descript[idx_value + 0] = (1./nr)       ;//* sw;
         row_descript[idx_value + 1] = (rr[0] / nr2) ;//* sw;

source/tests/test_compat_input.py

@@ -0,0 +1,32 @@
+import os,sys
+import numpy as np
+import unittest
+
+from deepmd.compat import convert_input_v0_v1
+from deepmd.common import j_loader
+
+class TestConvertInput (unittest.TestCase) :
+    def test_convert_smth(self):
+        jdata0 = j_loader(os.path.join('compat_inputs', 'water_se_a_v0.json'))
+        jdata1 = j_loader(os.path.join('compat_inputs', 'water_se_a_v1.json'))
+        jdata = convert_input_v0_v1(jdata0, warning = False, dump = None)
+        self.assertEqual(jdata, jdata1)
+
+    def test_convert_nonsmth(self):
+        jdata0 = j_loader(os.path.join('compat_inputs', 'water_v0.json'))
+        jdata1 = j_loader(os.path.join('compat_inputs', 'water_v1.json'))
+        jdata = convert_input_v0_v1(jdata0, warning = False, dump = None)
+        self.assertEqual(jdata, jdata1)
+
+    def test_json_yaml_equal(self):
+
+        inputs = ("water_v1", "water_se_a_v1")
+
+        for i in inputs:
+            jdata = j_loader(os.path.join('yaml_inputs', f'{i}.json'))
+            ydata = j_loader(os.path.join('yaml_inputs', f'{i}.yaml'))
+            self.assertEqual(jdata, ydata)
+
+        with self.assertRaises(TypeError):
+            j_loader("path_with_wrong.extension")
+

source/tests/test_data_modifier.py

@@ -1,9 +1,9 @@
-import os,sys,platform,json
+import os,sys,platform
 import numpy as np
 import unittest
 from deepmd.env import tf
 
-from deepmd.common import j_must_have, data_requirement
+from deepmd.common import j_must_have, data_requirement, j_loader
 from deepmd.RunOptions import RunOptions
 from deepmd.Trainer import NNPTrainer
 from deepmd.DataSystem import DeepmdDataSystem
@@ -45,8 +45,7 @@ def tearDown(self):
     def _setUp(self):
         args = Args()
         run_opt = RunOptions(args, False)
-        with open (args.INPUT, 'r') as fp:
-           jdata = json.load (fp)
+        jdata = j_loader(args.INPUT)
 
         # init model
         model = NNPTrainer (jdata, run_opt = run_opt)

source/tests/test_fitting_stat.py

@@ -1,10 +1,11 @@
-import os,sys,json
+import os,sys
 import numpy as np
 import unittest
 
 from collections import defaultdict
 from deepmd.DescrptSeA import DescrptSeA
 from deepmd.Fitting import EnerFitting
+from deepmd.common import j_loader
 
 input_json = 'water_se_a_afparam.json'
 
@@ -57,9 +58,8 @@ def _brute_aparam(data, ndim):
 
 class TestEnerFittingStat (unittest.TestCase) :
     def test (self) :
-        with open(input_json) as fp:
-            jdata = json.load(fp)
-            jdata = jdata['model']
+        jdata = j_loader(input_json)
+        jdata = jdata['model']
         descrpt = DescrptSeA(jdata['descriptor'])
         fitting = EnerFitting(jdata['fitting_net'], descrpt)
         avgs = [0, 10]

source/tests/test_model_loc_frame.py

@@ -1,4 +1,4 @@
-import dpdata,os,sys,json,unittest
+import dpdata,os,sys,unittest
 import numpy as np
 from deepmd.env import tf
 from common import Data,gen_data
@@ -8,7 +8,7 @@
 from deepmd.DescrptLocFrame import DescrptLocFrame
 from deepmd.Fitting import EnerFitting
 from deepmd.Model import Model
-from deepmd.common import j_must_have, j_must_have_d, j_have
+from deepmd.common import j_must_have, j_must_have_d, j_have, j_loader
 
 global_ener_float_precision = tf.float64
 global_tf_float_precision = tf.float64
@@ -21,8 +21,7 @@ def setUp(self) :
 
     def test_model(self):
         jfile = 'water.json'
-        with open(jfile) as fp:
-            jdata = json.load (fp)
+        jdata = j_loader(jfile)
         run_opt = RunOptions(None) 
         systems = j_must_have(jdata, 'systems')
         set_pfx = j_must_have(jdata, 'set_prefix')

source/tests/test_model_se_a.py

@@ -1,5 +1,5 @@
 
-import dpdata,os,sys,json,unittest
+import dpdata,os,sys,unittest
 import numpy as np
 from deepmd.env import tf
 from common import Data,gen_data
@@ -9,7 +9,7 @@
 from deepmd.DescrptSeA import DescrptSeA
 from deepmd.Fitting import EnerFitting
 from deepmd.Model import Model
-from deepmd.common import j_must_have, j_must_have_d, j_have
+from deepmd.common import j_must_have, j_must_have_d, j_have, j_loader
 
 global_ener_float_precision = tf.float64
 global_tf_float_precision = tf.float64
@@ -21,8 +21,8 @@ def setUp(self) :
 
     def test_model(self):
         jfile = 'water_se_a.json'
-        with open(jfile) as fp:
-            jdata = json.load (fp)
+        jdata = j_loader(jfile)
+
         run_opt = RunOptions(None) 
         systems = j_must_have(jdata, 'systems')
         set_pfx = j_must_have(jdata, 'set_prefix')