Adding LDA Transform

src/Microsoft.ML.Transforms/EntryPoints/TextAnalytics.cs

@@ -92,5 +92,20 @@ public static CommonOutputs.TransformOutput CharTokenize(IHostEnvironment env, C
                 OutputData = view
             };
         }
+
+        [TlcModule.EntryPoint(Name = "Transforms.LightLda", Desc = LdaTransform.Summary, UserName = LdaTransform.UserName, ShortName = LdaTransform.ShortName)]
+        public static CommonOutputs.TransformOutput LightLda(IHostEnvironment env, LdaTransform.Arguments input)
+        {
+            Contracts.CheckValue(env, nameof(env));
+            env.CheckValue(input, nameof(input));
+
+            var h = EntryPointUtils.CheckArgsAndCreateHost(env, "LightLda", input);
+            var view = new LdaTransform(h, input, input.Data);
+            return new CommonOutputs.TransformOutput()
+            {
+                Model = new TransformModel(h, view, input.Data),
+                OutputData = view
+            };
+        }
     }
 }

src/Microsoft.ML.Transforms/Text/LdaSingleBox.cs

@@ -0,0 +1,357 @@
+// Licensed to the .NET Foundation under one or more agreements.
+// The .NET Foundation licenses this file to you under the MIT license.
+// See the LICENSE file in the project root for more information.
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Runtime.InteropServices;
+using System.Security;
+
+namespace Microsoft.ML.Runtime.TextAnalytics
+{
+
+    internal static class LdaInterface
+    {
+        public struct LdaEngine
+        {
+            public IntPtr Ptr;
+        }
+
+        private const string NativeDll = "LdaNative";
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern LdaEngine CreateEngine(int numTopic, int numVocab, float alphaSum, float beta, int numIter,
+            int likelihoodInterval, int numThread, int mhstep, int maxDocToken);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void AllocateModelMemory(LdaEngine engine, int numTopic, int numVocab, long tableSize, long aliasTableSize);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void AllocateDataMemory(LdaEngine engine, int docNum, long corpusSize);
+
+        [DllImport(NativeDll, CharSet = CharSet.Ansi), SuppressUnmanagedCodeSecurity]
+        internal static extern void Train(LdaEngine engine, string trainOutput);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void GetModelStat(LdaEngine engine, out long memBlockSize, out long aliasMemBlockSize);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void Test(LdaEngine engine, int numBurninIter, float[] pLogLikelihood);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void CleanData(LdaEngine engine);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void CleanModel(LdaEngine engine);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void DestroyEngine(LdaEngine engine);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void GetWordTopic(LdaEngine engine, int wordId, int[] pTopic, int[] pProb, ref int length);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void SetWordTopic(LdaEngine engine, int wordId, int[] pTopic, int[] pProb, int length);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void SetAlphaSum(LdaEngine engine, float avgDocLength);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern int FeedInData(LdaEngine engine, int[] termId, int[] termFreq, int termNum, int numVocab);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern int FeedInDataDense(LdaEngine engine, int[] termFreq, int termNum, int numVocab);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void GetDocTopic(LdaEngine engine, int docId, int[] pTopic, int[] pProb, ref int numTopicReturn);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void GetTopicSummary(LdaEngine engine, int topicId, int[] pWords, float[] pProb, ref int numTopicReturn);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void TestOneDoc(LdaEngine engine, int[] termId, int[] termFreq, int termNum, int[] pTopics, int[] pProbs, ref int numTopicsMax, int numBurnIter, bool reset);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void TestOneDocDense(LdaEngine engine, int[] termFreq, int termNum, int[] pTopics, int[] pProbs, ref int numTopicsMax, int numBurninIter, bool reset);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void InitializeBeforeTrain(LdaEngine engine);
+
+        [DllImport(NativeDll), SuppressUnmanagedCodeSecurity]
+        internal static extern void InitializeBeforeTest(LdaEngine engine);
+    }
+
+    internal sealed class LdaSingleBox : IDisposable
+    {
+        private LdaInterface.LdaEngine _engine;
+        private bool _isDisposed;
+        private int[] _topics;
+        private int[] _probabilities;
+        private int[] _summaryTerm;
+        private float[] _summaryTermProb;
+        private readonly int _likelihoodInterval;
+        private readonly float _alpha;
+        private readonly float _beta;
+        private readonly int _mhStep;
+        private readonly int _numThread;
+        private readonly int _numSummaryTerms;
+        private readonly bool _denseOutput;
+
+        public readonly int NumTopic;
+        public readonly int NumVocab;
+        public LdaSingleBox(int numTopic, int numVocab, float alpha,
+                            float beta, int numIter, int likelihoodInterval, int numThread,
+                            int mhstep, int numSummaryTerms, bool denseOutput, int maxDocToken)
+        {
+            NumTopic = numTopic;
+            NumVocab = numVocab;
+            _alpha = alpha;
+            _beta = beta;
+            _mhStep = mhstep;
+            _numSummaryTerms = numSummaryTerms;
+            _denseOutput = denseOutput;
+            _likelihoodInterval = likelihoodInterval;
+            _numThread = numThread;
+
+            _topics = new int[numTopic];
+            _probabilities = new int[numTopic];
+
+            _summaryTerm = new int[_numSummaryTerms];
+            _summaryTermProb = new float[_numSummaryTerms];
+
+            _engine = LdaInterface.CreateEngine(numTopic, numVocab, alpha, beta, numIter, likelihoodInterval, numThread, mhstep, maxDocToken);
+        }
+
+        public void AllocateModelMemory(int numTopic, int numVocab, long tableSize, long aliasTableSize)
+        {
+            Contracts.Check(numTopic >= 0);
+            Contracts.Check(numVocab >= 0);
+            Contracts.Check(tableSize >= 0);
+            Contracts.Check(aliasTableSize >= 0);
+            LdaInterface.AllocateModelMemory(_engine, numVocab, numTopic, tableSize, aliasTableSize);
+        }
+
+        public void AllocateDataMemory(int docNum, long corpusSize)
+        {
+            Contracts.Check(docNum >= 0);
+            Contracts.Check(corpusSize >= 0);
+            LdaInterface.AllocateDataMemory(_engine, docNum, corpusSize);
+        }
+
+        public void Train(string trainOutput)
+        {
+            if (string.IsNullOrWhiteSpace(trainOutput))
+                LdaInterface.Train(_engine, null);
+            else
+                LdaInterface.Train(_engine, trainOutput);
+        }
+
+        public void GetModelStat(out long memBlockSize, out long aliasMemBlockSize)
+        {
+            LdaInterface.GetModelStat(_engine, out memBlockSize, out aliasMemBlockSize);
+        }
+
+        public void Test(int numBurninIter, float[] logLikelihood)
+        {
+            Contracts.Check(numBurninIter >= 0);
+            var pLogLikelihood = new float[numBurninIter];
+            LdaInterface.Test(_engine, numBurninIter, pLogLikelihood);
+            logLikelihood = pLogLikelihood.Select(item => (float)item).ToArray();
+        }
+
+        public void CleanData()
+        {
+            LdaInterface.CleanData(_engine);
+        }
+
+        public void CleanModel()
+        {
+            LdaInterface.CleanModel(_engine);
+        }
+
+        public void CopyModel(LdaSingleBox trainer, int wordId)
+        {
+            int length = NumTopic;
+            LdaInterface.GetWordTopic(trainer._engine, wordId, _topics, _probabilities, ref length);
+            LdaInterface.SetWordTopic(_engine, wordId, _topics, _probabilities, length);
+        }
+
+        public void SetAlphaSum(float averageDocLength)
+        {
+            LdaInterface.SetAlphaSum(_engine, averageDocLength);
+        }
+
+        public int LoadDoc(int[] termID, double[] termVal, int termNum, int numVocab)
+        {
+            Contracts.Check(numVocab == NumVocab);
+            Contracts.Check(termNum > 0);
+            Contracts.Check(termID.Length >= termNum);
+            Contracts.Check(termVal.Length >= termNum);
+
+            int[] pID = new int[termNum];
+            int[] pVal = termVal.Select(item => (int)item).ToArray();
+            Array.Copy(termID, pID, termNum);
+            return LdaInterface.FeedInData(_engine, pID, pVal, termNum, NumVocab);
+        }
+
+        public int LoadDocDense(double[] termVal, int termNum, int numVocab)
+        {
+            Contracts.Check(numVocab == NumVocab);
+            Contracts.Check(termNum > 0);
+
+            Contracts.Check(termVal.Length >= termNum);
+
+            int[] pID = new int[termNum];
+            int[] pVal = termVal.Select(item => (int)item).ToArray();
+            return LdaInterface.FeedInDataDense(_engine, pVal, termNum, NumVocab);
+
+        }
+
+        public List<KeyValuePair<int, float>> GetDocTopicVector(int docID)
+        {
+            int numTopicReturn = NumTopic;
+            LdaInterface.GetDocTopic(_engine, docID, _topics, _probabilities, ref numTopicReturn);
+            var topicRet = new List<KeyValuePair<int, float>>();
+            int currentTopic = 0;
+            for (int i = 0; i < numTopicReturn; i++)
+            {
+                if (_denseOutput)
+                {
+                    while (currentTopic < _topics[i])
+                    {
+                        //use a value to smooth the count so that we get dense output on each topic
+                        //the smooth value is usually set to 0.1 
+                        topicRet.Add(new KeyValuePair<int, float>(currentTopic, (float)_alpha));
+                        currentTopic++;
+                    }
+                    topicRet.Add(new KeyValuePair<int, float>(_topics[i], _probabilities[i] + (float)_alpha));
+                    currentTopic++;
+                }
+                else
+                {
+                    topicRet.Add(new KeyValuePair<int, float>(_topics[i], (float)_probabilities[i]));
+                }
+            }
+
+            if (_denseOutput)
+            {
+                while (currentTopic < NumTopic)
+                {
+                    topicRet.Add(new KeyValuePair<int, float>(currentTopic, (float)_alpha));
+                    currentTopic++;
+                }
+            }
+            return topicRet;
+        }
+
+        public List<KeyValuePair<int, float>> TestDoc(int[] termID, double[] termVal, int termNum, int numBurninIter, bool reset)
+        {
+            Contracts.Check(termNum > 0);
+            Contracts.Check(termVal.Length >= termNum);
+            Contracts.Check(termID.Length >= termNum);
+
+            int[] pID = new int[termNum];
+            int[] pVal = termVal.Select(item => (int)item).ToArray();
+            int[] pTopic = new int[NumTopic];
+            int[] pProb = new int[NumTopic];
+            Array.Copy(termID, pID, termNum);
+
+            int numTopicReturn = NumTopic;
+
+            LdaInterface.TestOneDoc(_engine, pID, pVal, termNum, pTopic, pProb, ref numTopicReturn, numBurninIter, reset);
+
+            // PREfast suspects that the value of numTopicReturn could be changed in _engine->TestOneDoc, which might result in read overrun in the following loop.
+            if (numTopicReturn > NumTopic)
+            {
+                Contracts.Check(false);
+                numTopicReturn = NumTopic;
+            }
+
+            var topicRet = new List<KeyValuePair<int, float>>();
+            for (int i = 0; i < numTopicReturn; i++)
+                topicRet.Add(new KeyValuePair<int, float>(pTopic[i], (float)pProb[i]));
+            return topicRet;
+        }
+
+        public List<KeyValuePair<int, float>> TestDocDense(double[] termVal, int termNum, int numBurninIter, bool reset)
+        {
+            Contracts.Check(termNum > 0);
+            Contracts.Check(numBurninIter > 0);
+            Contracts.Check(termVal.Length >= termNum);
+            int[] pVal = termVal.Select(item => (int)item).ToArray();
+            int[] pTopic = new int[NumTopic];
+            int[] pProb = new int[NumTopic];
+
+            int numTopicReturn = NumTopic;
+
+            // There are two versions of TestOneDoc interfaces
+            // (1) TestOneDoc
+            // (2) TestOneDocRestart
+            // The second one is the same as the first one except that it will reset
+            // the states of the internal random number generator, so that it yields reproducable results for the same input
+            LdaInterface.TestOneDocDense(_engine, pVal, termNum, pTopic, pProb, ref numTopicReturn, numBurninIter, reset);
+
+            // PREfast suspects that the value of numTopicReturn could be changed in _engine->TestOneDoc, which might result in read overrun in the following loop.
+            if (numTopicReturn > NumTopic)
+            {
+                Contracts.Check(false);
+                numTopicReturn = NumTopic;
+            }
+
+            var topicRet = new List<KeyValuePair<int, float>>();
+            for (int i = 0; i < numTopicReturn; i++)
+                topicRet.Add(new KeyValuePair<int, float>(pTopic[i], (float)pProb[i]));
+            return topicRet;
+        }
+
+        public void InitializeBeforeTrain()
+        {
+            LdaInterface.InitializeBeforeTrain(_engine);
+        }
+
+        public void InitializeBeforeTest()
+        {
+            LdaInterface.InitializeBeforeTest(_engine);
+        }
+
+        public KeyValuePair<int, int>[] GetModel(int wordId)
+        {
+            int length = NumTopic;
+            LdaInterface.GetWordTopic(_engine, wordId, _topics, _probabilities, ref length);
+            var wordTopicVector = new KeyValuePair<int, int>[length];
+
+            for (int i = 0; i < length; i++)
+                wordTopicVector[i] = new KeyValuePair<int, int>(_topics[i], _probabilities[i]);
+            return wordTopicVector;
+        }
+
+        public KeyValuePair<int, float>[] GetTopicSummary(int topicId)
+        {
+            int length = _numSummaryTerms;
+            LdaInterface.GetTopicSummary(_engine, topicId, _summaryTerm, _summaryTermProb, ref length);
+            var topicSummary = new KeyValuePair<int, float>[length];
+
+            for (int i = 0; i < length; i++)
+                topicSummary[i] = new KeyValuePair<int, float>(_summaryTerm[i], _summaryTermProb[i]);
+            return topicSummary;
+        }
+
+        public void SetModel(int termID, int[] topicID, int[] topicProb, int topicNum)
+        {
+            Contracts.Check(termID >= 0);
+            Contracts.Check(topicNum <= NumTopic);
+            Array.Copy(topicID, _topics, topicNum);
+            Array.Copy(topicProb, _probabilities, topicNum);
+            LdaInterface.SetWordTopic(_engine, termID, _topics, _probabilities, topicNum);
+        }
+
+        public void Dispose()
+        {
+            if (_isDisposed)
+                return;
+            _isDisposed = true;
+            LdaInterface.DestroyEngine(_engine);
+            _engine.Ptr = IntPtr.Zero;
+        }
+    }
+}