Remove useless input parameters: of_ml_nnode and of_ml_nlayer

Author: sunliang98

docs/advanced/input_files/input-main.md

@@ -212,8 +212,6 @@
   - [ML-KEDF: machine learning based kinetic energy density functional for OFDFT](#ml-kedf-machine-learning-based-kinetic-energy-density-functional-for-ofdft)
     - [of\_ml\_gene\_data](#of_ml_gene_data)
     - [of\_ml\_device](#of_ml_device)
-    - [of\_ml\_nnode](#of_ml_nnode)
-    - [of\_ml\_nlayer](#of_ml_nlayer)
     - [of\_ml\_feg](#of_ml_feg)
     - [of\_ml\_nkernel](#of_ml_nkernel)
     - [of\_ml\_kernel](#of_ml_kernel)
@@ -2269,20 +2267,6 @@ Warning: this function is not robust enough for the current version. Please try
   - **gpu**: GPU
 - **Default**: cpu
 
-### of_ml_nnode
-
-- **Type**: Integer
-- **Availability**: OFDFT
-- **Description**: Hyperparameter: number of node of hidden layer.
-- **Default**: 100
-
-### of_ml_nlayer
-
-- **Type**: Integer
-- **Availability**: OFDFT
-- **Description**: Hyperparameter: number of hidden layer.
-- **Default**: 3
-
 ### of_ml_feg
 
 - **Type**: Integer
@@ -2475,7 +2459,7 @@ Warning: this function is not robust enough for the current version. Please try
 
 - **Type**: Boolean
 - **Availability**: OFDFT
-- **Description**: For test. Read in the density, and output the F and Pauli potential.
+- **Description**: FOR TEST. Read in the density, and output the F and Pauli potential.
 - **Default**: False
 
 [back to top](#full-list-of-input-keywords)

source/module_esolver/esolver_of_interface.cpp

@@ -72,7 +72,7 @@ void ESolver_OF::init_kedf(const Input_para& inp)
             this->ml_ = new KEDF_ML();
         this->ml_->set_para(this->pw_rho->nrxx, this->dV_, this->nelec_[0], inp.of_tf_weight, inp.of_vw_weight, 
                         inp.of_ml_chi_p, inp.of_ml_chi_q, inp.of_ml_chi_xi, inp.of_ml_chi_pnl, inp.of_ml_chi_qnl,
-                        inp.of_ml_nnode, inp.of_ml_nlayer, inp.of_ml_nkernel, inp.of_ml_kernel, inp.of_ml_kernel_scaling,
+                        inp.of_ml_nkernel, inp.of_ml_kernel, inp.of_ml_kernel_scaling,
                         inp.of_ml_yukawa_alpha, inp.of_ml_kernel_file, inp.of_ml_gamma, inp.of_ml_p, inp.of_ml_q, inp.of_ml_tanhp, inp.of_ml_tanhq,
                         inp.of_ml_gammanl, inp.of_ml_pnl, inp.of_ml_qnl, inp.of_ml_xi, inp.of_ml_tanhxi,
                         inp.of_ml_tanhxi_nl, inp.of_ml_tanh_pnl, inp.of_ml_tanh_qnl, inp.of_ml_tanhp_nl, inp.of_ml_tanhq_nl, inp.of_ml_device, this->pw_rho);

source/module_hamilt_pw/hamilt_ofdft/kedf_ml.cpp

@@ -17,8 +17,6 @@ void KEDF_ML::set_para(
     const std::vector<double> &chi_xi,
     const std::vector<double> &chi_pnl,
     const std::vector<double> &chi_qnl,
-    const int nnode,
-    const int nlayer,
     const int &nkernel,
     const std::vector<int> &kernel_type,
     const std::vector<double> &kernel_scaling,
@@ -76,6 +74,8 @@ void KEDF_ML::set_para(
 
     if (PARAM.inp.of_kinetic == "ml")
     {
+        int nnode = 100;
+        int nlayer = 3;
         this->nn = std::make_shared<NN_OFImpl>(this->nx, 0, this->ninput, nnode, nlayer, this->device);
         torch::load(this->nn, "net.pt", this->device_type);
         std::cout << "load net done" << std::endl;

source/module_hamilt_pw/hamilt_ofdft/kedf_ml.h

@@ -33,8 +33,6 @@ class KEDF_ML
         const std::vector<double> &chi_xi,
         const std::vector<double> &chi_pnl,
         const std::vector<double> &chi_qnl,
-        const int nnode,
-        const int nlayer,
         const int &nkernel,
         const std::vector<int> &kernel_type,
         const std::vector<double> &kernel_scaling,

source/module_io/read_input_item_ofdft.cpp

@@ -221,18 +221,6 @@ void ReadInput::item_ofdft()
         read_sync_string(input.of_ml_device);
         this->add_item(item);
     }
-    {
-        Input_Item item("of_ml_nnode");
-        item.annotation = "Hyperparameter: number of node of hidden layer";
-        read_sync_int(input.of_ml_nnode);
-        this->add_item(item);
-    }
-    {
-        Input_Item item("of_ml_nlayer");
-        item.annotation = "Hyperparameter: number of hidden layer";
-        read_sync_int(input.of_ml_nlayer);
-        this->add_item(item);
-    }
     {
         Input_Item item("of_ml_feg");
         item.annotation = "The Free Electron Gas limit: 0: no, 3: yes";

source/module_parameter/input_parameter.h

@@ -212,10 +212,7 @@ struct Input_para
     bool of_ml_gene_data = false;                ///< Generate training data or not
     // device
     std::string of_ml_device = "cpu";                      ///< Run NN on GPU or CPU
-    // size of nn 2023-04-19
-    int of_ml_nnode = 100;                       ///< Hyperparameter: number of node of hidden layer
-    int of_ml_nlayer = 3;                        ///< Hyperparameter: number of hidden layer
-    int of_ml_feg = 0;                           ///< The Free Electron Gas limit: 0: no, 3: yes
+    int of_ml_feg = 0;                                     ///< The Free Electron Gas limit: 0: no, 3: yes
     // kernel
     int of_ml_nkernel = 1;                                 ///< Number of kernels
     std::vector<int> of_ml_kernel = {1};                   ///< Type of kernel, 1 for wt, 2 for yukawa, and 3 for TKK