int ParseFloats( const char *pText, float *pFloat, int count )
{
const char *pTemp = pText;
int index = 0;
while ( pTemp && count > 0 )
{
// Skip current token / float
pTemp = SkipText( pTemp );
// Skip any whitespace in between
pTemp = SkipSpace( pTemp );
if ( pTemp )
{
// Parse a float
pFloat[index] = (float)atof( pTemp );
count--;
index++;
}
}
if ( count == 0 )
return 1;
return 0;
}
/* <c5400> ../engine/tmessage.c:177 */
NOXREF int ParseFloats(const char *pText, float *pFloat, int count)
{
const char *pTemp = pText;
int index = 0;
while (pTemp && count > 0)
{
pTemp = SkipText(pTemp);
pTemp = SkipSpace(pTemp);
if (pTemp)
{
pFloat[index] = (float)Q_atof(pTemp);
count--;
index++;
}
}
if (count == 0)
return 1;
return 0;
}
bool NeuralNet::ParseNorms(char *pData)
{
// null vectors
int i;
for(i = 0; i < mNInp16; i++)
{
mpNormMeans16[i] = 0.0f;
mpNormDevs16[i] = 1.0f;
}
// mean vector
char *pt = pData;
pt = SkipSpaces(pt);
if(strncmp(pt, "vec", strlen("vec")) != 0)
{
return false;
}
pt += strlen("vec");
pt = SkipSpaces(pt);
int len;
if(!GetIntValue(pt, &len))
{
return false;
}
pt = SkipText(pt);
float *pvct = mpNormMeans16;
for(i = 0; i < mNInp; i++)
{
pt = SkipSpaces(pt);
if(!GetFloatValue(pt, pvct))
{
return false;
}
pvct++;
pt = SkipText(pt);
}
// standard deviation vector
pt = SkipSpaces(pt);
if(strncmp(pt, "vec", strlen("vec")) != 0)
{
return false;
}
pt += strlen("vec");
pt = SkipSpaces(pt);
if(!GetIntValue(pt, &len))
{
return false;
}
pt = SkipText(pt);
pvct = mpNormDevs16;
for(i = 0; i < mNInp; i++)
{
pt = SkipSpaces(pt);
if(!GetFloatValue(pt, pvct))
{
return false;
}
pvct++;
pt = SkipText(pt);
}
// puts("means");
// DumpMatrix(mpNormMeans16, 1, mNInp16, mNInp16);
// puts("devs");
// DumpMatrix(mpNormDevs16, 1, mNInp16, mNInp16);
return true;
}
bool NeuralNet::ParseWeights(char *pData)
{
// null matrixes
memset((void *)mpInpHidMatrix, 0, mNHid16 * mNInp16 * sizeof(float));
memset((void *)mpHidOutMatrix, 0, mNOut16 * mNHid16 * sizeof(float));
memset((void *)mpHiddenBiases, 0, mNHid16 * sizeof(float));
memset((void *)mpOutputBiases, 0, mNOut16 * sizeof(float));
// input to hidden matrix
char *pt = pData;
pt = SkipSpaces(pt);
if(strncmp(pt, "weigvec", strlen("weigvec")) != 0)
{
return false;
}
pt += strlen("weigvec");
pt = SkipSpaces(pt);
int n_inp_hid;
if(!GetIntValue(pt, &n_inp_hid))
{
return false;
}
pt = SkipText(pt);
float *pmat = mpInpHidMatrix16;
int i;
for(i = 0; i < mNHid; i++)
{
int j;
for(j = 0; j < mNInp; j++)
{
pt = SkipSpaces(pt);
if(!GetFloatValue(pt, pmat))
{
return false;
}
pmat++;
pt = SkipText(pt);
}
for(j = mNInp; j < mNInp16; j++)
{
*pmat = 0.0f;
pmat++;
}
}
// hidden to output matrix
pt = SkipSpaces(pt);
if(strncmp(pt, "weigvec", strlen("weigvec")) != 0)
{
return false;
}
pt += strlen("weigvec");
pt = SkipSpaces(pt);
int n_hid_out;
if(!GetIntValue(pt, &n_hid_out))
{
return false;
}
pt = SkipText(pt);
pmat = mpHidOutMatrix16;
for(i = 0; i < mNOut; i++)
{
int j;
for(j = 0; j < mNHid; j++)
{
pt = SkipSpaces(pt);
if(!GetFloatValue(pt, pmat))
{
return false;
}
pmat++;
pt = SkipText(pt);
}
for(j = mNHid; j < mNHid16; j++)
{
*pmat = 0.0f;
pmat++;
}
}
// hidden biases
pt = SkipSpaces(pt);
if(strncmp(pt, "biasvec", strlen("biasvec")) != 0)
{
return false;
}
pt += strlen("biasvec");
pt = SkipSpaces(pt);
int n_biases_hid;
if(!GetIntValue(pt, &n_biases_hid))
{
return false;
}
pt = SkipText(pt);
float *pvec = mpHiddenBiases16;
for(i = 0; i < mNHid; i++)
{
pt = SkipSpaces(pt);
if(!GetFloatValue(pt, pvec))
{
return false;
}
pvec++;
pt = SkipText(pt);
}
// output biases
pt = SkipSpaces(pt);
if(strncmp(pt, "biasvec", strlen("biasvec")) != 0)
{
return false;
}
pt += strlen("biasvec");
pt = SkipSpaces(pt);
int n_biases_out;
if(!GetIntValue(pt, &n_biases_out))
{
return false;
}
pt = SkipText(pt);
pvec = mpOutputBiases16;
for(i = 0; i < mNOut; i++)
{
pt = SkipSpaces(pt);
if(!GetFloatValue(pt, pvec))
{
return false;
}
pvec++;
pt = SkipText(pt);
}
return true;
}
