internal void InitializePretrained(LDAModel model)
{
_ldaTrainer.AllocateModelMemory(model.VocabularyBuckets, model.NumberOfTopics, model.MemBlockSize, model.AliasMemBlockSize);
Debug.Assert(model.VocabularyBuckets == model.LDA_Data.Length);
for (int termID = 0; termID < model.VocabularyBuckets; termID++)
{
var kvs = model.LDA_Data[termID];
var topicId = kvs.Select(kv => kv.Key).ToArray();
var topicProb = kvs.Select(kv => kv.Value).ToArray();
var termTopicNum = topicId.Length;
_ldaTrainer.SetModel(termID, topicId, topicProb, termTopicNum);
}
//do the preparation
if (!_predictionPreparationDone)
{
lock (_preparationSyncRoot)
{
_ldaTrainer.InitializeBeforeTest();
_predictionPreparationDone = true;
}
}
}
public LdaState(IExceptionContext ectx, ModelLoadContext ctx)
: this()
{
ectx.AssertValue(ctx);
// *** Binary format ***
// <ColInfoEx>
// int: vocabnum
// long: memblocksize
// long: aliasMemBlockSize
// (serializing term by term, for one term)
// int: term_id, int: topic_num, KeyValuePair<int, int>[]: termTopicVector
InfoEx = new ColInfoEx(ectx, ctx);
_numVocab = ctx.Reader.ReadInt32();
ectx.CheckDecode(_numVocab > 0);
long memBlockSize = ctx.Reader.ReadInt64();
ectx.CheckDecode(memBlockSize > 0);
long aliasMemBlockSize = ctx.Reader.ReadInt64();
ectx.CheckDecode(aliasMemBlockSize > 0);
_ldaTrainer = new LdaSingleBox(
InfoEx.NumTopic,
_numVocab, /* Need to set number of vocabulary here */
InfoEx.AlphaSum,
InfoEx.Beta,
InfoEx.NumIter,
InfoEx.LikelihoodInterval,
InfoEx.NumThread,
InfoEx.MHStep,
InfoEx.NumSummaryTermPerTopic,
false,
InfoEx.NumMaxDocToken);
_ldaTrainer.AllocateModelMemory(_numVocab, InfoEx.NumTopic, memBlockSize, aliasMemBlockSize);
for (int i = 0; i < _numVocab; i++)
{
int termID = ctx.Reader.ReadInt32();
ectx.CheckDecode(termID >= 0);
int termTopicNum = ctx.Reader.ReadInt32();
ectx.CheckDecode(termTopicNum >= 0);
int[] topicId = new int[termTopicNum];
int[] topicProb = new int[termTopicNum];
for (int j = 0; j < termTopicNum; j++)
{
topicId[j] = ctx.Reader.ReadInt32();
topicProb[j] = ctx.Reader.ReadInt32();
}
//set the topic into _ldaTrainer inner topic table
_ldaTrainer.SetModel(termID, topicId, topicProb, termTopicNum);
}
//do the preparation
if (!_predictionPreparationDone)
{
_ldaTrainer.InitializeBeforeTest();
_predictionPreparationDone = true;
}
}
