gistfile1.txt

/*

On Windows 7, run as follows:

rem Download mnist from http://yann.lecun.com/exdb/mnist/index.html
rem decompress into c:\mnist
rem rename to change the '.' to be a '-', in the filenames
rem then, in a cmd:
call $DEEPCLDIR\dist\bin\activate.sh
deepcl_train datadir=c:\mnist numtrain=1280 numtest=1280
c:\Windows\Microsoft.NET\Framework\v4.0.30319\csc.exe /debug test3_win.cs
test3_win.exe

Run as follows (tested on Ubuntu 16.04, using mono):

source $DEEPCLDIR/dist/bin/activate.sh
deepcl_train datadir=/norep/data/mnist/ numtrain=1280 numtest=1280
# this will create weights.dat
mcs test.cs
# creates test.exe
mono test.exe

*/

using System;
using System.Diagnostics;
using System.IO;
using System.Runtime.Serialization;
using System.Runtime.Serialization.Formatters.Binary;


public class HelloWorld
{
    static public void Main ()
    {
        Process network = new Process();

        network.StartInfo.RedirectStandardOutput = true;
        network.StartInfo.RedirectStandardInput = true;
        network.StartInfo.CreateNoWindow = false;
        network.StartInfo.UseShellExecute = false;
        network.StartInfo.FileName = "deepcl_predict";
        network.StartInfo.Arguments = "batchsize=1 outputfile=out.txt";
        network.Start();

        int batchSize = 9;
        int planes = 1;
        int imageSize = 28;
        float[,,,] floats = new float[batchSize, planes, imageSize, imageSize];
        Random random = new Random();
        for(int n = 0; n < batchSize; n++) {
            for(int p = 0; p < planes; p++) {
                for(int h = 0; h < imageSize; h++) {
                    for(int w = 0; w < imageSize; w++) {
                        floats[n,p,h,w] = (float)random.NextDouble();
                    }
                }
            }
        }
        int[] dims = new int[3];
        dims[0] = planes;
        dims[1] = imageSize;
        dims[2] = imageSize;

        using (Stream myOutStream = Console.OpenStandardOutput())
        {
            for(int i = 0; i < 3; i++) {
                byte[] bytes = BitConverter.GetBytes(dims[i]);
                network.StandardInput.BaseStream.Write(bytes, 0, bytes.Length);
            }
            Console.WriteLine("sent header");
            for(int it = 0; it < 10; it++) {
                for(int n = 0; n < batchSize; n++) {
                    for(int p = 0; p < planes; p++) {
                        for(int h = 0; h < imageSize; h++) {
                            for(int w = 0; w < imageSize; w++) {
                                float somefloat = (float)random.NextDouble();
                                byte[] bytes = BitConverter.GetBytes(somefloat);
                                if( h == 0) {
                                    bytes[0] = 10;
                                    bytes[1] = 12;
                                    bytes[2] = 13;
                                }
                                network.StandardInput.BaseStream.Write(bytes, 0, bytes.Length);
                            }
                        }
                    }
                }
                network.StandardInput.BaseStream.Flush();
                Console.WriteLine("sent batch");
                //for(int i = 0; i < batchSize; i++ ) {
                    int count = 0;
                    while(count < batchSize) {
                    string outstring = network.StandardOutput.ReadLine();
                    Console.WriteLine(outstring);
                    if(outstring.Substring(0, 1) == "0") {
                        count += 1;
                        Console.WriteLine("count " + count);
                    }
                    }
                  //  Console.WriteLine();
                //}
                Console.WriteLine("read batch " + it);
                Console.ReadLine();
            }
        }
    }
}