Support Ewald

examples/water/train/polar.json

@@ -31,9 +31,9 @@
 
     "learning_rate" :{
 	"type":		"exp",
-	"start_lr":	0.001,
 	"decay_steps":	5000,
-	"decay_rate":	0.95,
+	"start_lr":	0.001,	
+	"stop_lr":	3.51e-8,
 	"_comment":	"that's all"
     },
 

examples/water/train/polar_se_a.json

@@ -3,7 +3,7 @@
     "_comment": " model parameters",
     "model":{
 	"type_map":		["O", "H"],
-	"data_stat_nbatch":	1,
+	"data_stat_nbatch":	10,
 	"descriptor" :{
 	    "type":		"se_a",
 	    "sel":		[46, 92],
@@ -18,7 +18,7 @@
 	"fitting_net": {
 	    "type":		"polar",
 	    "sel_type":		[0],
-	    "fit_diag":		true,
+	    "fit_diag":		false,
 	    "neuron":		[100, 100, 100],
 	    "resnet_dt":	true,
 	    "seed":		1,
@@ -29,9 +29,9 @@
 
     "learning_rate" :{
 	"type":		"exp",
-	"start_lr":	0.01,
 	"decay_steps":	5000,
-	"decay_rate":	0.95,
+	"start_lr":	0.01,
+	"stop_lr":	3.51e-7,
 	"_comment":	"that's all"
     },
 

examples/water/train/wannier.json

@@ -32,9 +32,9 @@
 
     "learning_rate" :{
 	"type":		"exp",
-	"start_lr":	0.001,
 	"decay_steps":	5000,
-	"decay_rate":	0.95,
+	"start_lr":	0.001,	
+	"stop_lr":	3.51e-8,
 	"_comment":	"that's all"
     },
 

examples/water/train/water.json

@@ -3,6 +3,7 @@
     "_comment": " model parameters",
     "model":{
 	"type_map":		["O", "H"],
+	"data_stat_nbatch":	10,
 	"descriptor": {
 	    "type":		"loc_frame",
 	    "sel_a":		[16, 32],
@@ -28,9 +29,9 @@
 
     "learning_rate" :{
 	"type":		"exp",
-	"start_lr":	0.001,
 	"decay_steps":	5000,
-	"decay_rate":	0.95,
+	"start_lr":	0.001,
+	"stop_lr":	3.51e-8,
 	"_comment":	"that's all"
     },
 

examples/water/train/water_se_a.json

@@ -24,9 +24,9 @@
 
     "learning_rate" :{
 	"type":		"exp",
-	"start_lr":	0.001,
 	"decay_steps":	5000,
-	"decay_rate":	0.95,
+	"start_lr":	0.001,	
+	"stop_lr":	3.51e-8,
 	"_comment":	"that's all"
     },
 

examples/water/train/water_se_ar.json

@@ -35,9 +35,9 @@
 
     "learning_rate" :{
 	"type":		"exp",
-	"start_lr":	0.005,
 	"decay_steps":	5000,
-	"decay_rate":	0.95,
+	"start_lr":	0.005,
+	"stop_lr":	1.76e-7,
 	"_comment":	"that's all"
     },
 

examples/water/train/water_se_r.json

@@ -23,9 +23,10 @@
     },
 
     "learning_rate" : {
-	"start_lr":	0.005,
+	"type":		"exp",
 	"decay_steps":	5000,
-	"decay_rate":	0.95,
+	"start_lr":	0.005,	
+	"stop_lr":	1.76e-7,
 	"_comment":	" that's all"
     },
 

examples/water/train/water_srtab_example.json

@@ -32,9 +32,9 @@
 
     "learning_rate" :{
 	"type":		"exp",
-	"start_lr":	0.001,
 	"decay_steps":	5000,
-	"decay_rate":	0.95,
+	"start_lr":	0.001,	
+	"stop_lr":	3.51e-8,
 	"_comment":	"that's all"
     },
 

source/lib/include/DataModifier.h

@@ -0,0 +1,50 @@
+#pragma once
+
+#include "NNPInter.h"
+
+class DataModifier
+{
+public:
+  DataModifier();
+  DataModifier(const string & model, 
+	       const int & gpu_rank = 0, 
+	       const string & name_scope = "");
+  ~DataModifier () {};
+  void init (const string & model, 
+	     const int & gpu_rank = 0, 
+	     const string & name_scope = "");
+  void print_summary(const string &pre) const;
+public:
+  void compute (vector<VALUETYPE> &		dfcorr_,
+		vector<VALUETYPE> &		dvcorr_,
+		const vector<VALUETYPE> &	dcoord_,
+		const vector<int> &		datype_,
+		const vector<VALUETYPE> &	dbox, 
+		const vector<pair<int,int>> &	pairs,
+		const vector<VALUETYPE> &	delef_, 
+		const int			nghost,
+		const LammpsNeighborList &	lmp_list);
+  VALUETYPE cutoff () const {assert(inited); return rcut;};
+  int numb_types () const {assert(inited); return ntypes;};
+  vector<int> sel_types () const {assert(inited); return sel_type;};
+private:
+  Session* session;
+  string name_scope, name_prefix;
+  int num_intra_nthreads, num_inter_nthreads;
+  GraphDef graph_def;
+  bool inited;
+  VALUETYPE rcut;
+  VALUETYPE cell_size;
+  int ntypes;
+  string model_type;
+  vector<int> sel_type;
+  template<class VT> VT get_scalar(const string & name) const;
+  template<class VT> void get_vector(vector<VT> & vec, const string & name) const;
+  void run_model (vector<VALUETYPE> &		dforce,
+		  vector<VALUETYPE> &		dvirial,
+		  Session *			session,
+		  const std::vector<std::pair<string, Tensor>> & input_tensors,
+		  const NNPAtomMap<VALUETYPE> &	nnpmap,
+		  const int			nghost);
+};
+

source/lib/include/DeepTensor.h

@@ -0,0 +1,63 @@
+#pragma once
+
+#include "NNPInter.h"
+
+class DeepTensor
+{
+public:
+  DeepTensor();
+  DeepTensor(const string & model, 
+	     const int & gpu_rank = 0, 
+	     const string &name_scope = "");
+  void init (const string & model, 
+	     const int & gpu_rank = 0, 
+	     const string &name_scope = "");
+  void print_summary(const string &pre) const;
+public:
+  void compute (vector<VALUETYPE> &		value,
+		const vector<VALUETYPE> &	coord,
+		const vector<int> &		atype,
+		const vector<VALUETYPE> &	box,
+		const int			nghost = 0);
+  void compute (vector<VALUETYPE> &		value,
+		const vector<VALUETYPE> &	coord,
+		const vector<int> &		atype,
+		const vector<VALUETYPE> &	box, 
+		const int			nghost,
+		const LammpsNeighborList &	lmp_list);
+  VALUETYPE cutoff () const {assert(inited); return rcut;};
+  int numb_types () const {assert(inited); return ntypes;};
+  int output_dim () const {assert(inited); return odim;};
+  const vector<int> & sel_types () const {assert(inited); return sel_type;};
+private:
+  Session* session;
+  string name_scope;
+  int num_intra_nthreads, num_inter_nthreads;
+  GraphDef graph_def;
+  bool inited;
+  VALUETYPE rcut;
+  VALUETYPE cell_size;
+  int ntypes;
+  string model_type;
+  int odim;
+  vector<int> sel_type;
+  template<class VT> VT get_scalar(const string & name) const;
+  template<class VT> void get_vector (vector<VT> & vec, const string & name) const;
+  void run_model (vector<VALUETYPE> &		d_tensor_,
+		  Session *			session, 
+		  const std::vector<std::pair<string, Tensor>> & input_tensors,
+		  const NNPAtomMap<VALUETYPE> &	nnpmap, 
+		  const int			nghost = 0);
+  void compute_inner (vector<VALUETYPE> &	value,
+		      const vector<VALUETYPE> &	coord,
+		      const vector<int> &	atype,
+		      const vector<VALUETYPE> &	box,
+		      const int			nghost = 0);
+  void compute_inner (vector<VALUETYPE> &	value,
+		      const vector<VALUETYPE> &	coord,
+		      const vector<int> &	atype,
+		      const vector<VALUETYPE> &	box, 
+		      const int			nghost,
+		      const InternalNeighborList&lmp_list);
+};
+