Port transductive alignment model

[pmachapman]

Fixes #455.

Port of sillsdev/machine.py#327

@ddaspit I am unsure whether my implementations of ThotSymmetrizedWordAlignmentModel.TrainingAlignmentCount and ThotWordAlignmentModel.GetTrainingAlignment() are correct. I wrote them based on what I understood the underlying logic in thot to be doing, as SymmetrizedAlignmentModel is not exposed via the C API.

If they are not right, I will update thot to expose the methods from SymmetrizedAlignmentModel in the C API that are exposed in thot's module.cc and used by the machine.py implementation.

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This change is 

[ddaspit]

@ddaspit reviewed 9 files and all commit messages, and made 3 comments.
Reviewable status: 9 of 10 files reviewed, 3 unresolved discussions (waiting on Enkidu93 and pmachapman).

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src/SIL.Machine/Corpora/CorporaExtensions.cs line 1135 at r1 (raw file):

        }

        public static IParallelTextCorpus WordAlign(

I think there are too many pitfalls with trying to implement this operation. Instead, we should add a similar IParallelTextCorpus extension method in SIL.Machine.Translation.Thot that trains and aligns a corpus using a Thot model. The method should accept a ThotWordAlignmentModelType parameter. You can have overloads that accept a ThotWordAlignmentModel or ThotSymmetrizedWordAlignmentModel as well. It would mimic the word_align_corpus function in Machine.py. If the passed in model is not configured to emit training alignments, then it should fall back to inductive alignment.

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src/SIL.Machine.Translation.Thot/ThotWordAlignmentModel.cs line 169 at r1 (raw file):

        {
            CheckDisposed();
            IntPtr nativeMatrix = Thot.AllocNativeMatrix(_sourceWords.Count, _targetWords.Count);

To get the size of the matrix, you can call swAlignModel_getTrainingAlignment with a null buffer.

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src/SIL.Machine.Translation.Thot/ThotWordAlignmentModelTrainer.cs line 24 at r1 (raw file):

        private readonly bool _isEflomal;

        public ThotWordAlignmentModelTrainer(

You forgot emitTrainingAlignments here.