// Preferences.cpp: implementation of the CPreferences class.
//
//////////////////////////////////////////////////////////////////////
#include "stdafx.h"
#include "MNist.h"
#include "Preferences.h"
#ifdef _DEBUG
#undef THIS_FILE
static char THIS_FILE[]=__FILE__;
#define new DEBUG_NEW
#endif
//////////////////////////////////////////////////////////////////////
// Construction/Destruction
//////////////////////////////////////////////////////////////////////
CPreferences::CPreferences() : m_pMainApp( NULL )
{
}
CPreferences::~CPreferences()
{
}
void CPreferences::ReadIniFile(CWinApp *pApp)
{
ASSERT( m_pMainApp==NULL && pApp!=NULL );
m_pMainApp = pApp;
// confirm that INI file exists, and write a default one from resources if it does not
WIN32_FIND_DATA fd;
HANDLE hFile = ::FindFirstFile( m_pMainApp->m_pszProfileName, &fd );
if ( hFile == INVALID_HANDLE_VALUE )
{
// file must not exist -- get default ini file from resources and
// write it to ..\YourAppName.ini (which is stored in m_pMainApp->m_pszProfileName)
CFile f;
CFileException fe;
if ( f.Open( (LPCTSTR) m_pMainApp->m_pszProfileName,
CFile::modeCreate | CFile::modeWrite, &fe ) ) // note: didn't specify modeNoTruncate, so length is zero'd
{
HINSTANCE hInst = m_pMainApp->m_hInstance;
HRSRC hINI = ::FindResource(hInst,
MAKEINTRESOURCE( IDR_TEXT_DEFAULT_INI ),
_T("TEXT") );
DWORD size = ::SizeofResource(hInst, hINI);
HGLOBAL hGlobal = ::LoadResource(hInst, hINI);
LPVOID t = ::LockResource(hGlobal);
f.Write( t, size );
f.Close();
::FreeResource(hGlobal);
}
else
{
::MessageBox( NULL,
_T("Error encountered while trying to write default INI file\n")
_T("Hard-coded baseline parameters will be used instead"),
_T("INI File Creation Failed"),
MB_OK | MB_ICONWARNING);
}
}
::FindClose( hFile );
#if 0
// set default values
m_nMagicTrainingLabels = 0x00000801;
m_nMagicTrainingImages = 0x00000803;
m_nItemsTrainingLabels = 60000;
m_nItemsTrainingImages = 60000;
m_nMagicTestingLabels = 0x00000801;
m_nMagicTestingImages = 0x00000803;
m_nItemsTestingLabels = 10000;
m_nItemsTestingImages = 10000;
m_nRowsImages = g_cImageSize;
m_nColsImages = g_cImageSize;
m_nMagWindowSize = 5;
m_nMagWindowMagnification = 8;
m_dInitialEtaLearningRate = 0.001;
m_dLearningRateDecay = 0.794328235; // 0.794328235 = 0.001 down to 0.00001 in 20 epochs
m_dMinimumEtaLearningRate = 0.00001;
m_nAfterEveryNBackprops = 60000;
m_cNumBackpropThreads = 2;
m_cNumTestingThreads = 1;
// parameters for controlling distortions of input image
m_dMaxScaling = 15.0; // like 20.0 for 20%
m_dMaxRotation = 15.0; // like 20.0 for 20 degrees
m_dElasticSigma = 8.0; // higher numbers are more smooth and less distorted; Simard uses 4.0
m_dElasticScaling = 0.5; // higher numbers amplify the distortions; Simard uses 34 (sic, maybe 0.34 ??)
// for limiting the step size in backpropagation, since we are using second order
// "Stochastic Diagonal Levenberg-Marquardt" update algorithm. See Yann LeCun 1998
// "Gradient-Based Learning Applied to Document Recognition" at page 41
m_dMicronLimitParameter = 0.10; // since we divide by this, update can never be more than 10x current eta
m_nNumHessianPatterns = 500; // number of patterns used to calculate the diagonal Hessian
#endif
// now read values from the ini file
CString tSection;
// Neural Network parameters
tSection = _T( "Neural Network Parameters" );
Get( tSection, _T( "Initial learning rate (eta)" ), m_dInitialEtaLearningRate );
Get( tSection, _T( "Minimum learning rate (eta)" ), m_dMinimumEtaLearningRate );
Get( tSection, _T( "Rate of decay for learning rate (eta)" ), m_dLearningRateDecay );
Get( tSection, _T( "Decay rate is applied after this number of backprops" ), m_nAfterEveryNBackprops );
Get( tSection, _T( "Number of backprop threads" ), m_cNumBackpropThreads );
Get( tSection, _T( "Number of testing threads" ), m_cNumTestingThreads );
Get( tSection, _T( "Number of patterns used to calculate Hessian" ), m_nNumHessianPatterns );
Get( tSection, _T( "Limiting divisor (micron) for learning rate amplification (like 0.10 for 10x limit)" ), m_dMicronLimitParameter );
// Neural Network Viewer parameters
tSection = _T( "Neural Net Viewer Parameters" );
Get( tSection, _T( "Size of magnification window" ), m_nMagWindowSize );
Get( tSection, _T( "Magnification factor for magnification window" ), m_nMagWindowMagnification );
// MNIST data collection parameters
tSection = _T( "MNIST Database Parameters" );
Get( tSection, _T( "Training images magic number" ), m_nMagicTrainingImages );
Get( tSection, _T( "Training images item count" ), m_nItemsTrainingImages );
Get( tSection, _T( "Training labels magic number" ), m_nMagicTrainingLabels );
Get( tSection, _T( "Training labels item count" ), m_nItemsTrainingLabels );
Get( tSection, _T( "Testing images magic number" ), m_nMagicTestingImages );
Get( tSection, _T( "Testing images item count" ), m_nItemsTestingImages );
Get( tSection, _T( "Testing labels magic number" ), m_nMagicTestingLabels );
Get( tSection, _T( "Testing labels item count" ), m_nItemsTestingLabels );
// these two are basically ignored
UINT uiCount = g_cImageSize;
Get( tSection, _T( "Rows per image" ), uiCount );
m_nRowsImages = uiCount;
uiCount = g_cImageSize;
Get( tSection, _T( "Columns per image" ), uiCount );
m_nColsImages = uiCount;
// parameters for controlling pattern distortion during backpropagation
tSection = _T( "Parameters for Controlling Pattern Distortion During Backpropagation" );
Get( tSection, _T( "Maximum scale factor change (percent, like 20.0 for 20%)" ), m_dMaxScaling );
Get( tSection, _T( "Maximum rotational change (degrees, like 20.0 for 20 degrees)" ), m_dMaxRotation );
Get( tSection, _T( "Sigma for elastic distortions (higher numbers are more smooth and less distorted; Simard uses 4.0)" ), m_dElasticSigma );
Get( tSection, _T( "Scaling for elastic distortions (higher numbers amplify distortions; Simard uses 0.34)" ), m_dElasticScaling );
}
// overloaded "Get" functions. Each of these functions should be called with a default
// value already stored in the data type; if the entry exists in the INI file then that value
// is returned, else the default value is unchanged and it is also stored into the INI file
// for future use
// NOTE: Do not use with the MS data type BOOL. If used with type BOOL, then the "int" version
// will be called. Use the c-standard data type "bool" instead
void CPreferences::Get(LPCTSTR strSection, LPCTSTR strEntry, UINT &uiVal)
{
union { UINT ui; int ii; } iInput, iRet;
iInput.ui = uiVal;
iRet.ii = m_pMainApp->GetProfileInt( strSection, strEntry, iInput.ii );
uiVal = iRet.ui;
}
void CPreferences::Get(LPCTSTR strSection, LPCTSTR strEntry, int &iVal)
{
int iRet = m_pMainApp->GetProfileInt( strSection, strEntry, iVal );
iVal = iRet;
}
void CPreferences::Get(LPCTSTR strSection, LPCTSTR strEntry, float &fVal)
{
CString strTemp;
double dVal = (double)fVal;
strTemp.Format( _T("g"), dVal );
CString sRet = m_pMainApp->GetProfileString( strSection, strEntry, strTemp );
dVal = _tcstod( (LPCTSTR)sRet, NULL );
fVal = (float)dVal;
}
void CPreferences::Get(LPCTSTR strSection, LPCTSTR strEntry, double &dVal)
{
CString strTemp;
strTemp.Format( _T("g"), dVal );
CString sRet = m_pMainApp->GetProfileString( strSection, strEntry, strTemp );
dVal = _tcstod( (LPCTSTR)sRet, NULL );
}
void CPreferences::Get(LPCTSTR strSection, LPCTSTR strEntry, LPTSTR pStrVal)
{
CString sRet = m_pMainApp->GetProfileString( strSection, strEntry, pStrVal );
_tcscpy( pStrVal, (LPCTSTR)sRet );
}
void CPreferences::Get(LPCTSTR strSection, LPCTSTR strEntry, CString &strVal)
{
CString sRet = m_pMainApp->GetProfileString( strSection, strEntry, strVal );
strVal = sRet;
}
void CPreferences::Get(LPCTSTR strSection, LPCTSTR strEntry, bool &bVal)
{
CString strTemp;
strTemp = ( bVal==false ) ? ( _T( "No" ) ) : ( _T( "Yes" ) );
CString sRet = m_pMainApp->GetProfileString( strSection, strEntry, strTemp );
// check for "no", "false" or zero("0")
sRet.MakeUpper();
if ( sRet[0] == _T( 'N' ) ||
sRet[0] == _T( 'F' ) ||
sRet[0] == _T( '0' ) )
{
bVal = FALSE;
}
else
{
bVal = TRUE;
}
}
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