Merge pull request #159 from amcadmus/master

fix bug of test data, a few compiling bugs

Author: amcadmus

.travis.yml

@@ -72,7 +72,7 @@ matrix:
       - CXX=g++-8
       - TENSORFLOW_VERSION=2.0
 before_install:
-  - pip install --upgrade pip
+#  - pip install --upgrade pip
   - pip install --upgrade setuptools
   - pip install tensorflow==$TENSORFLOW_VERSION
 install:

source/CMakeLists.txt

@@ -173,7 +173,7 @@ if (BUILD_CPP_IF)
   if (USE_CUDA_TOOLKIT)
     set (LIB_DEEPMD_OP_CUDA		"deepmd_op_cuda")
   else()
-    set (LIB_DEEPMD_OP_CUDA		"")
+    set (LIB_DEEPMD_OP_CUDA		"deepmd_op")
   endif()
   if (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER_EQUAL 4.9)
     set (LIB_DEEPMD_NATIVE	"deepmd_native_md")

source/lib/include/NNPInter.h

@@ -112,8 +112,8 @@ class NNPInter
   GraphDef graph_def;
   bool inited;
   template<class VT> VT get_scalar(const string & name) const;
-  VALUETYPE get_rcut () const;
-  int get_ntypes () const;
+  // VALUETYPE get_rcut () const;
+  // int get_ntypes () const;
   VALUETYPE rcut;
   VALUETYPE cell_size;
   int ntypes;
@@ -210,8 +210,8 @@ class NNPInterModelDevi
   vector<GraphDef> graph_defs;
   bool inited;
   template<class VT> VT get_scalar(const string name) const;
-  VALUETYPE get_rcut () const;
-  int get_ntypes () const;
+  // VALUETYPE get_rcut () const;
+  // int get_ntypes () const;
   VALUETYPE rcut;
   VALUETYPE cell_size;
   int ntypes;

source/lib/src/NNPInter.cc

@@ -849,8 +849,8 @@ init (const string & model, const int & gpu_rank)
   ntypes = get_scalar<int>("descrpt_attr/ntypes");
   dfparam = get_scalar<int>("fitting_attr/dfparam");
   daparam = get_scalar<int>("fitting_attr/daparam");
-  assert(rcut == get_rcut());
-  assert(ntypes == get_ntypes());
+  // assert(rcut == get_rcut());
+  // assert(ntypes == get_ntypes());
   if (dfparam < 0) dfparam = 0;
   if (daparam < 0) daparam = 0;
   inited = true;
@@ -880,8 +880,8 @@ init (const string & model, const int & gpu_rank)
   ntypes = get_scalar<int>("descrpt_attr/ntypes");
   dfparam = get_scalar<int>("fitting_attr/dfparam");
   daparam = get_scalar<int>("fitting_attr/daparam");
-  assert(rcut == get_rcut());
-  assert(ntypes == get_ntypes());
+  // assert(rcut == get_rcut());
+  // assert(ntypes == get_ntypes());
   if (dfparam < 0) dfparam = 0;
   if (daparam < 0) daparam = 0;
   // rcut = get_rcut();

source/train/test.py

@@ -6,7 +6,6 @@
 import argparse
 import numpy as np
 
-from deepmd.Data import DataSets
 from deepmd.Data import DeepmdData
 from deepmd import DeepEval
 from deepmd import DeepPot
@@ -35,13 +34,15 @@ def test_ener (args) :
     if args.rand_seed is not None :
         np.random.seed(args.rand_seed % (2**32))
 
-    data = DataSets (args.system, args.set_prefix, shuffle_test = args.shuffle_test)
+    dp = DeepPot(args.model)
+    data = DeepmdData(args.system, args.set_prefix, shuffle_test = args.shuffle_test, type_map = dp.get_type_map())
+
     test_data = data.get_test ()
     numb_test = args.numb_test
     natoms = len(test_data["type"][0])
     nframes = test_data["box"].shape[0]
     numb_test = min(nframes, numb_test)
-    dp = DeepPot(args.model)
+
     coord = test_data["coord"][:numb_test].reshape([numb_test, -1])
     box = test_data["box"][:numb_test]
     atype = test_data["type"][0]