Update the file names of nnof

Author: sunliang98

source/module_hamilt_pw/hamilt_ofdft/ml_tools/CMakeLists.txt

@@ -21,7 +21,7 @@ else()
 endif()
 include_directories(${libnpy_SOURCE_DIR}/include)
 
-add_executable(nnof main.cpp data.cpp nn_of.cpp grid.cpp input.cpp kernel.cpp pauli_potential.cpp train.cpp)
+add_executable(nnof main.cpp data.cpp nn_of.cpp grid.cpp input.cpp kernel.cpp pauli_potential.cpp train_kedf.cpp)
 target_link_libraries(nnof "${TORCH_LIBRARIES}")
 set_property(TARGET nnof PROPERTY CXX_STANDARD 14)
 

source/module_hamilt_pw/hamilt_ofdft/ml_tools/main.cpp

@@ -1,15 +1,12 @@
-#include "./train.h"
-// #include <sstream>
-// #include <math.h>
-// #include "time.h"
+#include "./train_kedf.h"
 
 int main()
 {
     torch::set_default_dtype(caffe2::TypeMeta::fromScalarType(torch::kDouble));
     auto output = torch::get_default_dtype();
     std::cout << "Default type: " << output << std::endl;
 
-    Train train;
+    Train_KEDF train;
     train.input.readInput();
     if (train.input.check_pot)
     {
@@ -20,29 +17,4 @@ int main()
         train.init();
         train.train();
     }
-
-    // torch::Tensor x = torch::ones({2,2});
-    // x[0][0] = 0.;
-    // x[1][0] = 2.;
-    // x[1][1] = 3.;
-    // x.requires_grad_(true);
-    // std::cout << "x" << x << std::endl;
-    // torch::Tensor y = x * x + x.t() * x.t();
-    // std::cout << "y" << y << std::endl;
-    // std::vector<torch::Tensor> tmp_pot;
-    // std::vector<torch::Tensor> tmp_ipt;
-    // std::vector<torch::Tensor> tmp_eye;
-    // tmp_pot.push_back(y);
-    // tmp_ipt.push_back(x);
-    // tmp_eye.push_back(x);
-    // // tmp_eye.push_back(torch::ones_like(y));
-    // std::vector<torch::Tensor> tmp_grad;
-    // tmp_grad = torch::autograd::grad(tmp_pot, tmp_ipt, tmp_eye, true, true, true);
-    // std::cout << tmp_grad[0] << std::endl;
-
-    // load test
-    // std::shared_ptr<NN_OFImpl> nn = std::make_shared<NN_OFImpl>(64000, 6);
-    // torch::load(nn, "./net.pt");
-    // nn->setData(train.gamma, train.gammanl, train.p, train.pnl, train.q, train.qnl);
-    // std::cout << nn->forward(nn->inputs);
 }

source/module_hamilt_pw/hamilt_ofdft/ml_tools/pauli_potential.h

@@ -1,5 +1,5 @@
-#ifndef POTENTIAL_H
-#define POTENTIAL_H
+#ifndef PAULI_POTENTIAL_H
+#define PAULI_POTENTIAL_H
 
 #include <torch/torch.h>
 #include "./input.h"

source/module_hamilt_pw/hamilt_ofdft/ml_tools/train.cpp renamed to source/module_hamilt_pw/hamilt_ofdft/ml_tools/train_kedf.cpp

@@ -1,17 +1,17 @@
-#include "./train.h"
+#include "./train_kedf.h"
 #include <sstream>
 #include <math.h>
 #include <chrono>
 
-Train::~Train()
+Train_KEDF::~Train_KEDF()
 {
     delete[] this->train_volume;
     delete[] this->vali_volume;
     delete[] this->kernel_train;
     delete[] this->kernel_vali;
 }
 
-void Train::setUpFFT()
+void Train_KEDF::setUpFFT()
 {
     this->train_volume = new double[this->input.ntrain];
     this->grid_train.initGrid(
@@ -66,7 +66,7 @@ void Train::setUpFFT()
     // this->dumpTensor(this->fft_kernel_vali[0].reshape({this->data_train.nx}), "kernel_bcc.npy", this->data_train.nx);
 }
 
-void Train::set_device()
+void Train_KEDF::set_device()
 {
     if (this->input.device_type == "cpu")
     {
@@ -89,7 +89,7 @@ void Train::set_device()
     }
 }
 
-void Train::init_input_index()
+void Train_KEDF::init_input_index()
 {
     this->ninput = 0;
 
@@ -195,7 +195,7 @@ void Train::init_input_index()
     std::cout << "feg_limit = " << this->input.feg_limit << std::endl;
 }
 
-void Train::init()
+void Train_KEDF::init()
 {
     this->set_device();
     this->init_input_index();
@@ -214,18 +214,18 @@ void Train::init()
     this->nn->set_data(&(this->data_vali), this->descriptor_type, this->kernel_index, this->nn->input_vali);
 }
 
-torch::Tensor Train::lossFunction(torch::Tensor enhancement, torch::Tensor target, torch::Tensor coef)
+torch::Tensor Train_KEDF::lossFunction(torch::Tensor enhancement, torch::Tensor target, torch::Tensor coef)
 {
     return torch::sum(torch::pow(enhancement - target, 2))/this->data_train.nx/coef/coef;
 }
 
-torch::Tensor Train::lossFunction_new(torch::Tensor enhancement, torch::Tensor target, torch::Tensor weight, torch::Tensor coef)
+torch::Tensor Train_KEDF::lossFunction_new(torch::Tensor enhancement, torch::Tensor target, torch::Tensor weight, torch::Tensor coef)
 {
     return torch::sum(torch::pow(weight * (enhancement - target), 2.))/this->data_train.nx/coef/coef;
 }
 
 
-void Train::train()
+void Train_KEDF::train()
 {
     // time
     double tot = 0.;
@@ -239,7 +239,7 @@ void Train::train()
 
     start = std::chrono::high_resolution_clock::now();
 
-    std::cout << "========== Train begin ==========" << std::endl;
+    std::cout << "========== Train_KEDF begin ==========" << std::endl;
     // torch::Tensor target = (this->input.loss=="energy") ? this->data_train.enhancement : this->data_train.pauli;
     if (this->input.loss == "potential" || this->input.loss == "both" || this->input.loss == "both_new")
     {
@@ -427,7 +427,7 @@ void Train::train()
     std::cout << "Step\t\t\t"           << totStep  << "\t\t" << totStep/tot    * 100. << " %" << std::endl;
 }
 
-void Train::potTest()
+void Train_KEDF::potTest()
 {
     this->set_device();
     this->init_input_index();

source/module_hamilt_pw/hamilt_ofdft/ml_tools/train.h renamed to source/module_hamilt_pw/hamilt_ofdft/ml_tools/train_kedf.h

@@ -1,5 +1,5 @@
-#ifndef TRAIN_H
-#define TRAIN_H
+#ifndef TRAIN_KEDF_H
+#define TRAIN_KEDF_H
 
 #include "./data.h"
 #include "./grid.h"
@@ -10,11 +10,11 @@
 
 #include <torch/torch.h>
 
-class Train
+class Train_KEDF
 {
   public:
-    Train(){};
-    ~Train();
+    Train_KEDF(){};
+    ~Train_KEDF();
 
     std::shared_ptr<NN_OFImpl> nn;
     Input input;