create XTrainer

source/tensor/XLink.h

@@ -26,8 +26,6 @@
 #ifndef __XLINK_H__
 #ifndef __XLINK_H__
 #define __XLINK_H__
 #define __XLINK_H__
 
 
-#include "XGlobal.h"
-
 namespace nts{ // namespace nts(NiuTrans.Tensor)
 namespace nts{ // namespace nts(NiuTrans.Tensor)
 
 
 /* cross reference */
 /* cross reference */

source/trainer/XTrainer.cpp

+/* NiuTrans.Tensor - an open-source tensor library
+* Copyright (C) 2021
+* Natural Language Processing Lab, Northeastern University
+* and
+* NiuTrans Research
+* All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*   http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/*
+*
+* $Created by: XIAO Tong (xiaotong@mail.neu.edu.cn) 2021-02-23
+*
+*/
+
+#include "XTrainer.h"
+
+/* the nts (NiuTrans.Tensor) namespace */
+namespace nts {
+
+/* constructor */
+XTrainer::XTrainer()
+{
+}
+
+/* de-constructor */
+XTrainer::~XTrainer()
+{
+}
+
+} /* end of the nts (NiuTrans.Tensor) namespace */
\ No newline at end of file

source/trainer/XTrainer.h

+/* NiuTrans.Tensor - an open-source tensor library
+* Copyright (C) 2021
+* Natural Language Processing Lab, Northeastern University
+* and
+* NiuTrans Research
+* All rights reserved.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*   http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/*
+* This class organizes the training process of neural models, e.g., nmt and lm models
+* Distributed training is supported.
+*
+* $Created by: XIAO Tong (xiaotong@mail.neu.edu.cn) 2021-02-23
+* I start coding in 2021 after one year since I typed last C code.
+* BUT i was a GOOD tex writter in 2020 :)
+*/
+
+#ifndef __XTRAINER_H__
+#define __XTRAINER_H__
+
+#include "../network/XNet.h"
+#include "../tensor/XQueue.h"
+
+namespace nts { // namespace nts(NiuTrans.Tensor)
+
+/* 
+Training of neural networks with gradient methods. Here we suppose that we 
+are training NLP models. The routine could be:
+   
+1). initialize all we need
+2). data preparation
+3). loop until convergence
+    a). read a batch of samples from the input file
+    b). reset the worker
+    c). forward computation with the input
+    d). backward computation with respect to the loss
+    e). collect the gradient (neccessary when several workers are available)
+    f). update the model (on the server end)
+    g). distribute the new model to each worker
+
+Here a worker processes a batch of samples one time, and works with
+other workers independently. The server is the origanizer. It distriute
+the job to the workers and maintain the model.
+*/
+class XTrainer
+{
+private:
+
+public:
+    /* constructor */
+    XTrainer();
+
+    /* de-constructor */
+    ~XTrainer();
+};
+}
+#endif // __XTRAINER_H__
\ No newline at end of file