Convert LdaTransform to IEstimator/ITransformer API #1410
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| // 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. | ||||||||
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| using Microsoft.ML.Core.Data; | ||||||||
| using Microsoft.ML.Runtime; | ||||||||
| using Microsoft.ML.Runtime.Data; | ||||||||
| using Microsoft.ML.StaticPipe.Runtime; | ||||||||
| using Microsoft.ML.Transforms.Text; | ||||||||
| using System; | ||||||||
| using System.Collections.Generic; | ||||||||
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| namespace Microsoft.ML.StaticPipe | ||||||||
| { | ||||||||
| /// <summary> | ||||||||
| /// Information on the result of fitting a LDA transform. | ||||||||
| /// </summary> | ||||||||
| public sealed class LdaFitResult | ||||||||
| { | ||||||||
| /// <summary> | ||||||||
| /// For user defined delegates that accept instances of the containing type. | ||||||||
| /// </summary> | ||||||||
| /// <param name="result"></param> | ||||||||
| public delegate void OnFit(LdaFitResult result); | ||||||||
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| public LatentDirichletAllocationTransformer.LdaSummary LdaTopicSummary; | ||||||||
| public LdaFitResult(LatentDirichletAllocationTransformer.LdaSummary ldaTopicSummary) | ||||||||
| { | ||||||||
| LdaTopicSummary = ldaTopicSummary; | ||||||||
| } | ||||||||
| } | ||||||||
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| public static class LdaStaticExtensions | ||||||||
| { | ||||||||
| private struct Config | ||||||||
| { | ||||||||
| public readonly int NumTopic; | ||||||||
| public readonly Single AlphaSum; | ||||||||
| public readonly Single Beta; | ||||||||
|
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| public readonly int MHStep; | ||||||||
| public readonly int NumIter; | ||||||||
| public readonly int LikelihoodInterval; | ||||||||
| public readonly int NumThread; | ||||||||
| public readonly int NumMaxDocToken; | ||||||||
| public readonly int NumSummaryTermPerTopic; | ||||||||
| public readonly int NumBurninIter; | ||||||||
| public readonly bool ResetRandomGenerator; | ||||||||
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| public readonly Action<LatentDirichletAllocationTransformer.LdaSummary> OnFit; | ||||||||
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| public Config(int numTopic, Single alphaSum, Single beta, int mhStep, int numIter, int likelihoodInterval, | ||||||||
| int numThread, int numMaxDocToken, int numSummaryTermPerTopic, int numBurninIter, bool resetRandomGenerator, | ||||||||
| Action<LatentDirichletAllocationTransformer.LdaSummary> onFit) | ||||||||
| { | ||||||||
| NumTopic = numTopic; | ||||||||
| AlphaSum = alphaSum; | ||||||||
| Beta = beta; | ||||||||
| MHStep = mhStep; | ||||||||
| NumIter = numIter; | ||||||||
| LikelihoodInterval = likelihoodInterval; | ||||||||
| NumThread = numThread; | ||||||||
| NumMaxDocToken = numMaxDocToken; | ||||||||
| NumSummaryTermPerTopic = numSummaryTermPerTopic; | ||||||||
| NumBurninIter = numBurninIter; | ||||||||
| ResetRandomGenerator = resetRandomGenerator; | ||||||||
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| OnFit = onFit; | ||||||||
| } | ||||||||
| } | ||||||||
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| private static Action<LatentDirichletAllocationTransformer.LdaSummary> Wrap(LdaFitResult.OnFit onFit) | ||||||||
| { | ||||||||
| if (onFit == null) | ||||||||
| return null; | ||||||||
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| return ldaTopicSummary => onFit(new LdaFitResult(ldaTopicSummary)); | ||||||||
| } | ||||||||
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| private interface ILdaCol | ||||||||
| { | ||||||||
| PipelineColumn Input { get; } | ||||||||
| Config Config { get; } | ||||||||
| } | ||||||||
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| private sealed class ImplVector : Vector<float>, ILdaCol | ||||||||
| { | ||||||||
| public PipelineColumn Input { get; } | ||||||||
| public Config Config { get; } | ||||||||
| public ImplVector(PipelineColumn input, Config config) : base(Rec.Inst, input) | ||||||||
| { | ||||||||
| Input = input; | ||||||||
| Config = config; | ||||||||
| } | ||||||||
| } | ||||||||
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| private sealed class Rec : EstimatorReconciler | ||||||||
| { | ||||||||
| public static readonly Rec Inst = new Rec(); | ||||||||
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| public override IEstimator<ITransformer> Reconcile(IHostEnvironment env, | ||||||||
| PipelineColumn[] toOutput, | ||||||||
| IReadOnlyDictionary<PipelineColumn, string> inputNames, | ||||||||
| IReadOnlyDictionary<PipelineColumn, string> outputNames, | ||||||||
| IReadOnlyCollection<string> usedNames) | ||||||||
| { | ||||||||
| var infos = new LatentDirichletAllocationTransformer.ColumnInfo[toOutput.Length]; | ||||||||
| Action<LatentDirichletAllocationTransformer> onFit = null; | ||||||||
| for (int i = 0; i < toOutput.Length; ++i) | ||||||||
| { | ||||||||
| var tcol = (ILdaCol)toOutput[i]; | ||||||||
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| infos[i] = new LatentDirichletAllocationTransformer.ColumnInfo(inputNames[tcol.Input], outputNames[toOutput[i]], | ||||||||
| tcol.Config.NumTopic, | ||||||||
| tcol.Config.AlphaSum, | ||||||||
| tcol.Config.Beta, | ||||||||
| tcol.Config.MHStep, | ||||||||
| tcol.Config.NumIter, | ||||||||
| tcol.Config.LikelihoodInterval, | ||||||||
| tcol.Config.NumThread, | ||||||||
| tcol.Config.NumMaxDocToken, | ||||||||
| tcol.Config.NumSummaryTermPerTopic, | ||||||||
| tcol.Config.NumBurninIter, | ||||||||
| tcol.Config.ResetRandomGenerator); | ||||||||
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| if (tcol.Config.OnFit != null) | ||||||||
| { | ||||||||
| int ii = i; // Necessary because if we capture i that will change to toOutput.Length on call. | ||||||||
| onFit += tt => tcol.Config.OnFit(tt.GetLdaDetails(ii)); | ||||||||
| } | ||||||||
| } | ||||||||
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| var est = new LatentDirichletAllocationEstimator(env, infos); | ||||||||
| if (onFit == null) | ||||||||
| return est; | ||||||||
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| return est.WithOnFitDelegate(onFit); | ||||||||
| } | ||||||||
| } | ||||||||
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| /// <include file='doc.xml' path='doc/members/member[@name="LightLDA"]/*' /> | ||||||||
| /// <param name="input">A vector of floats representing the document.</param> | ||||||||
| /// <param name="numTopic">The number of topics.</param> | ||||||||
| /// <param name="alphaSum">Dirichlet prior on document-topic vectors.</param> | ||||||||
| /// <param name="beta">Dirichlet prior on vocab-topic vectors.</param> | ||||||||
| /// <param name="mhstep">Number of Metropolis Hasting step.</param> | ||||||||
| /// <param name="numIterations">Number of iterations.</param> | ||||||||
| /// <param name="likelihoodInterval">Compute log likelihood over local dataset on this iteration interval.</param> | ||||||||
| /// <param name="numThreads">The number of training threads. Default value depends on number of logical processors.</param> | ||||||||
| /// <param name="numMaxDocToken">The threshold of maximum count of tokens per doc.</param> | ||||||||
| /// <param name="numSummaryTermPerTopic">The number of words to summarize the topic.</param> | ||||||||
| /// <param name="numBurninIterations">The number of burn-in iterations.</param> | ||||||||
| /// <param name="resetRandomGenerator">Reset the random number generator for each document.</param> | ||||||||
| /// <param name="onFit">Called upon fitting with the learnt enumeration on the dataset.</param> | ||||||||
|
There was a problem hiding this comment. Sprinkle it with dots at the end of sentence. #Resolved |
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| public static Vector<float> ToLdaTopicVector(this Vector<float> input, | ||||||||
| int numTopic = LatentDirichletAllocationEstimator.Defaults.NumTopic, | ||||||||
| Single alphaSum = LatentDirichletAllocationEstimator.Defaults.AlphaSum, | ||||||||
| Single beta = LatentDirichletAllocationEstimator.Defaults.Beta, | ||||||||
| int mhstep = LatentDirichletAllocationEstimator.Defaults.Mhstep, | ||||||||
| int numIterations = LatentDirichletAllocationEstimator.Defaults.NumIterations, | ||||||||
| int likelihoodInterval = LatentDirichletAllocationEstimator.Defaults.LikelihoodInterval, | ||||||||
| int numThreads = LatentDirichletAllocationEstimator.Defaults.NumThreads, | ||||||||
| int numMaxDocToken = LatentDirichletAllocationEstimator.Defaults.NumMaxDocToken, | ||||||||
| int numSummaryTermPerTopic = LatentDirichletAllocationEstimator.Defaults.NumSummaryTermPerTopic, | ||||||||
| int numBurninIterations = LatentDirichletAllocationEstimator.Defaults.NumBurninIterations, | ||||||||
| bool resetRandomGenerator = LatentDirichletAllocationEstimator.Defaults.ResetRandomGenerator, | ||||||||
| LdaFitResult.OnFit onFit = null) | ||||||||
| { | ||||||||
| Contracts.CheckValue(input, nameof(input)); | ||||||||
| return new ImplVector(input, | ||||||||
| new Config(numTopic, alphaSum, beta, mhstep, numIterations, likelihoodInterval, numThreads, numMaxDocToken, numSummaryTermPerTopic, | ||||||||
| numBurninIterations, resetRandomGenerator, Wrap(onFit))); | ||||||||
| } | ||||||||
| } | ||||||||
| } | ||||||||
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