private void applyUnigramWeight()
{
float num = this.logMath.linearToLog((double)this.unigramWeight);
float num2 = this.logMath.linearToLog((double)(1f - this.unigramWeight));
float num3 = this.logMath.linearToLog((double)(1f / (float)this.numberNGrams[0]));
float num4 = this.logMath.linearToLog(this.wip);
float logVal = num3 + num2;
for (int i = 0; i < this.numberNGrams[0]; i++)
{
UnigramProbability unigramProbability = this.unigrams[i];
float num5 = unigramProbability.getLogProbability();
if (i != this.startWordID)
{
num5 += num;
num5 = this.logMath.addAsLinear(num5, logVal);
}
if (this.applyLanguageWeightAndWip)
{
num5 = num5 * this.languageWeight + num4;
unigramProbability.setLogBackoff(unigramProbability.getLogBackoff() * this.languageWeight);
}
unigramProbability.setLogProbability(num5);
}
}
protected internal virtual void loadModelLayout(InputStream inputStream)
{
DataInputStream dataInputStream = new DataInputStream(new BufferedInputStream(inputStream));
this.readHeader(dataInputStream);
this.unigrams = this.readUnigrams(dataInputStream, this.numberNGrams[0] + 1, this.bigEndian);
this.skipNGrams(dataInputStream);
int i;
for (i = 1; i < this.maxNGram; i++)
{
if (this.numberNGrams[i] > 0)
{
if (i == 1)
{
this.NGramProbTable[i] = this.readFloatTable(dataInputStream, this.bigEndian);
}
else
{
this.NGramBackoffTable[i] = this.readFloatTable(dataInputStream, this.bigEndian);
this.NGramProbTable[i] = this.readFloatTable(dataInputStream, this.bigEndian);
int j = 1 << this.logNGramSegmentSize;
int num = this.numberNGrams[i - 1] + 1;
int num2 = j;
int num3 = ((num2 != -1) ? (num / num2) : (-num)) + 1;
this.NGramSegmentTable[i] = this.readIntTable(dataInputStream, this.bigEndian, num3);
}
}
}
i = this.readInt(dataInputStream, this.bigEndian);
if (i <= 0)
{
string text = new StringBuilder().append("Bad word string size: ").append(i).toString();
throw new Error(text);
}
this.words = this.readWords(dataInputStream, i, this.numberNGrams[0]);
if (this.startWordID > -1)
{
UnigramProbability unigramProbability = this.unigrams[this.startWordID];
unigramProbability.setLogProbability(-99f);
}
if (this.endWordID > -1)
{
UnigramProbability unigramProbability = this.unigrams[this.endWordID];
unigramProbability.setLogBackoff(-99f);
}
this.applyUnigramWeight();
if (this.applyLanguageWeightAndWip)
{
for (int j = 0; j <= this.maxNGram; j++)
{
this.applyLanguageWeight(this.NGramProbTable[j], this.languageWeight);
this.applyWip(this.NGramProbTable[j], this.wip);
if (j > 1)
{
this.applyLanguageWeight(this.NGramBackoffTable[j], this.languageWeight);
}
}
}
dataInputStream.close();
}
