SetData.cpp

/*
 * NiuTrans.Tensor - an open-source tensor library
 * Copyright (C) 2018, Natural Language Processing Lab, Northestern University.
 * 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 (email: xiaotong@mail.neu.edu.cn) 2018-05-08
 */

#include "SetData.h"
#include "CopyValues.h"

#if !defined( WIN32 ) && !defined( _WIN32 )
    #include "sys/time.h"
    #include "time.h"
    #include "iconv.h"
#else
    #include "time.h"
    #include "windows.h"
    #include "process.h"
#endif

namespace nts{ // namespace nts(NiuTrans.Tensor)

/*
generate data items with a uniform distribution in [low,high]
>> tensor - the tensor whose data array would be initialized
>> low - lower value of the range
>> high - higher value of the range
*/
void SetDataRand(XTensor * tensor, DTYPE low, DTYPE high)
{
    if(tensor == NULL)
        return;
    
    /* GPU code */
    if(tensor->devID < 0){
        DTYPE variance = high - low;
        
        srand((unsigned)time(NULL));
        
        if(tensor->dataType == X_FLOAT){
            float * d = (float*)tensor->data;
            for(int i = 0; i < tensor->unitNum; i++){
                d[i] = variance * ((float)rand()/RAND_MAX) + low;
            }
        }
        else if(tensor->dataType == X_DOUBLE){
            double * d = (double*)tensor->data;
            for(int i = 0; i < tensor->unitNum; i++){
                d[i] = variance * ((double)rand()/RAND_MAX) + low;
            }
        }
        else{
            ShowNTErrors("TODO");
        }
    }
    /* GPU code
       The trick here is that initialize the data on a temperary tensor on CPU.
       The CPU data is then copied to GPU.
       TODO: generate data points on GPUs straightforwardly.
    */
    else{
        XTensor * t2 = NewTensor(tensor->order, tensor->dimSize, tensor->dataType, tensor->denseRatio, -1);
        SetDataRand(t2, low, high);
        CopyValues(t2, tensor);
        delete t2;
    }
}
    
} // namespace nts(NiuTrans.Tensor)