mpe implement

1 files changed, 409 insertions, 0 deletions

diff --git a/kaldi_seq/src/kaldi_mpe.cpp b/kaldi_seq/src/kaldi_mpe.cpp
new file mode 100644
index 0000000..5c4f7fc
--- /dev/null
+++ b/kaldi_seq/src/kaldi_mpe.cpp
@@ -0,0 +1,409 @@
+#include <string>
+#include "base/kaldi-common.h"
+#include "util/common-utils.h"
+#include "tree/context-dep.h"
+#include "hmm/transition-model.h"
+#include "fstext/fstext-lib.h"
+#include "decoder/faster-decoder.h"
+#include "decoder/decodable-matrix.h"
+#include "lat/kaldi-lattice.h"
+#include "lat/lattice-functions.h"
+
+#include "nnet/nnet-trnopts.h"
+#include "nnet/nnet-component.h"
+#include "nnet/nnet-activation.h"
+#include "nnet/nnet-nnet.h"
+#include "nnet/nnet-pdf-prior.h"
+#include "nnet/nnet-utils.h"
+#include "base/timer.h"
+#include "cudamatrix/cu-device.h"
+
+typedef kaldi::BaseFloat BaseFloat;
+typedef struct Matrix NervMatrix;
+
+namespace kaldi {
+    namespace nnet1 {
+
+        void LatticeAcousticRescore(const Matrix<BaseFloat> &log_like,
+                const TransitionModel &trans_model,
+                const std::vector<int32> &state_times,
+                Lattice *lat) {
+            kaldi::uint64 props = lat->Properties(fst::kFstProperties, false);
+            if (!(props & fst::kTopSorted))
+                KALDI_ERR << "Input lattice must be topologically sorted.";
+
+            KALDI_ASSERT(!state_times.empty());
+            std::vector<std::vector<int32> > time_to_state(log_like.NumRows());
+            for (size_t i = 0; i < state_times.size(); i++) {
+                KALDI_ASSERT(state_times[i] >= 0);
+                if (state_times[i] < log_like.NumRows())  // end state may be past this..
+                    time_to_state[state_times[i]].push_back(i);
+                else
+                    KALDI_ASSERT(state_times[i] == log_like.NumRows()
+                            && "There appears to be lattice/feature mismatch.");
+            }
+
+            for (int32 t = 0; t < log_like.NumRows(); t++) {
+                for (size_t i = 0; i < time_to_state[t].size(); i++) {
+                    int32 state = time_to_state[t][i];
+                    for (fst::MutableArcIterator<Lattice> aiter(lat, state); !aiter.Done();
+                            aiter.Next()) {
+                        LatticeArc arc = aiter.Value();
+                        int32 trans_id = arc.ilabel;
+                        if (trans_id != 0) {  // Non-epsilon input label on arc
+                            int32 pdf_id = trans_model.TransitionIdToPdf(trans_id);
+                            arc.weight.SetValue2(-log_like(t, pdf_id) + arc.weight.Value2());
+                            aiter.SetValue(arc);
+                        }
+                    }
+                }
+            }
+        }
+
+    }  // namespace nnet1
+}  // namespace kaldi
+
+
+extern "C" {
+#include "kaldi_mpe.h"
+#include "string.h"
+#include "assert.h"
+#include "nerv/common.h"
+
+    extern NervMatrix *nerv_matrix_host_float_create(long nrow, long ncol, Status *status);
+    extern void nerv_matrix_host_float_copy_fromd(NervMatrix *mat, const NervMatrix *cumat, int, int, int, Status *);
+    using namespace kaldi;
+    using namespace kaldi::nnet1;
+    typedef kaldi::int32 int32;
+
+    struct KaldiMPE {
+        TransitionModel *trans_model;
+        RandomAccessLatticeReader *den_lat_reader;
+        RandomAccessInt32VectorReader *ref_ali_reader;
+
+        Lattice den_lat;
+        vector<int32> state_times;
+
+        PdfPriorOptions *prior_opts;
+        PdfPrior *log_prior;
+
+        std::vector<int32> silence_phones;
+        std::vector<int32> ref_ali;
+
+        Timer *time;
+        double time_now;
+
+        int32 num_done, num_no_ref_ali, num_no_den_lat, num_other_error;
+
+        kaldi::int64 total_frames;
+        int32 num_frames;
+        double total_frame_acc, utt_frame_acc;
+
+        bool binary;
+        bool one_silence_class;
+        BaseFloat acoustic_scale, lm_scale, old_acoustic_scale;
+        kaldi::int32 max_frames;
+        bool do_smbr;
+        std::string use_gpu;
+    };
+
+    KaldiMPE * new_KaldiMPE(const char* arg, const char* mdl, const char* lat, const char* ali)
+    {
+        KaldiMPE * mpe = new KaldiMPE;
+
+        const char *usage =
+            "Perform iteration of Neural Network MPE/sMBR training by stochastic "
+            "gradient descent.\n"
+            "The network weights are updated on each utterance.\n"
+            "Usage:  nnet-train-mpe-sequential [options] <model-in> <transition-model-in> "
+            "<feature-rspecifier> <den-lat-rspecifier> <ali-rspecifier> [<model-out>]\n"
+            "e.g.: \n"
+            " nnet-train-mpe-sequential nnet.init trans.mdl scp:train.scp scp:denlats.scp ark:train.ali "
+            "nnet.iter1\n";
+
+        ParseOptions po(usage);
+
+        NnetTrainOptions trn_opts; trn_opts.learn_rate=0.00001;
+        trn_opts.Register(&po);
+
+        mpe->binary = true;
+        po.Register("binary", &(mpe->binary), "Write output in binary mode");
+
+        std::string feature_transform;
+        po.Register("feature-transform", &feature_transform,
+                "Feature transform in Nnet format");
+        std::string silence_phones_str;
+        po.Register("silence-phones", &silence_phones_str, "Colon-separated list "
+                "of integer id's of silence phones, e.g. 46:47");
+
+        mpe->prior_opts = new PdfPriorOptions;
+        PdfPriorOptions &prior_opts = *(mpe->prior_opts);
+        prior_opts.Register(&po);
+
+        mpe->one_silence_class = false;
+        mpe->acoustic_scale = 1.0,
+            mpe->lm_scale = 1.0,
+            mpe->old_acoustic_scale = 0.0;
+        po.Register("acoustic-scale", &(mpe->acoustic_scale),
+                "Scaling factor for acoustic likelihoods");
+        po.Register("lm-scale", &(mpe->lm_scale),
+                "Scaling factor for \"graph costs\" (including LM costs)");
+        po.Register("old-acoustic-scale", &(mpe->old_acoustic_scale),
+                "Add in the scores in the input lattices with this scale, rather "
+                "than discarding them.");
+        po.Register("one-silence-class", &(mpe->one_silence_class), "If true, newer "
+                "behavior which will tend to reduce insertions.");
+        mpe->max_frames = 6000; // Allow segments maximum of one minute by default
+        po.Register("max-frames",&(mpe->max_frames), "Maximum number of frames a segment can have to be processed");
+        mpe->do_smbr = false;
+        po.Register("do-smbr", &(mpe->do_smbr), "Use state-level accuracies instead of "
+                "phone accuracies.");
+
+        mpe->use_gpu=std::string("yes");
+        po.Register("use-gpu", &(mpe->use_gpu), "yes|no|optional, only has effect if compiled with CUDA");
+
+        int narg = 0;
+        char args[64][1024];
+        char *token;
+        char *saveptr = NULL;
+        char tmpstr[1024];
+
+        strcpy(tmpstr, arg);
+        strcpy(args[0], "nnet-train-mpe-sequential");
+        for(narg = 1, token = strtok_r(tmpstr, " ", &saveptr); token; token = strtok_r(NULL, " ", &saveptr))
+            strcpy(args[narg++], token);
+        strcpy(args[narg++], "0.nnet");
+        strcpy(args[narg++], mdl);
+        strcpy(args[narg++], "feat");
+        strcpy(args[narg++], lat);
+        strcpy(args[narg++], ali);
+        strcpy(args[narg++], "1.nnet");
+
+        char **argsv = new char*[narg];
+        for(int _i = 0; _i < narg; _i++)
+            argsv[_i] = args[_i];
+
+        po.Read(narg, argsv);
+        delete [] argsv;
+
+        if (po.NumArgs() != 6) {
+            po.PrintUsage();
+            exit(1);
+        }
+
+        std::string transition_model_filename = po.GetArg(2),
+            den_lat_rspecifier = po.GetArg(4),
+            ref_ali_rspecifier = po.GetArg(5);
+
+        std::vector<int32> &silence_phones = mpe->silence_phones;
+        if (!kaldi::SplitStringToIntegers(silence_phones_str, ":", false,
+                    &silence_phones))
+            KALDI_ERR << "Invalid silence-phones string " << silence_phones_str;
+        kaldi::SortAndUniq(&silence_phones);
+        if (silence_phones.empty())
+            KALDI_LOG << "No silence phones specified.";
+
+        // Select the GPU
+#if HAVE_CUDA == 1
+        CuDevice::Instantiate().SelectGpuId(use_gpu);
+#endif
+
+        // Read the class-frame-counts, compute priors
+        mpe->log_prior = new PdfPrior(prior_opts);
+        PdfPrior &log_prior = *(mpe->log_prior);
+
+        // Read transition model
+        mpe->trans_model = new TransitionModel;
+        ReadKaldiObject(transition_model_filename, mpe->trans_model);
+
+        mpe->den_lat_reader = new RandomAccessLatticeReader(den_lat_rspecifier);
+        mpe->ref_ali_reader = new RandomAccessInt32VectorReader(ref_ali_rspecifier);
+
+        mpe->time = new Timer;
+        mpe->time_now = 0;
+        mpe->num_done =0;
+        mpe->num_no_ref_ali = 0;
+        mpe->num_no_den_lat = 0;
+        mpe->num_other_error = 0;
+        mpe->total_frames = 0;
+        mpe->total_frame_acc = 0.0;
+        mpe->utt_frame_acc = 0.0;
+
+        return mpe;
+    }
+
+    void destroy_KaldiMPE(KaldiMPE *mpe)
+    {
+        delete mpe->trans_model;
+        delete mpe->den_lat_reader;
+        delete mpe->ref_ali_reader;
+        delete mpe->time;
+        delete mpe->prior_opts;
+        delete mpe->log_prior;
+    }
+
+    int check_mpe(KaldiMPE *mpe, const NervMatrix* mat, const char *key)
+    {
+        std::string utt(key);
+        if (!mpe->den_lat_reader->HasKey(utt)) {
+            KALDI_WARN << "Utterance " << utt << ": found no lattice.";
+            mpe->num_no_den_lat++;
+            return 0;
+        }
+        if (!mpe->ref_ali_reader->HasKey(utt)) {
+            KALDI_WARN << "Utterance " << utt << ": found no reference alignment.";
+            mpe->num_no_ref_ali++;
+            return 0;
+        }
+
+        assert(sizeof(BaseFloat) == sizeof(float));
+        // 1) get the features, numerator alignment
+        mpe->ref_ali = mpe->ref_ali_reader->Value(utt);
+        long mat_nrow = mat->nrow, mat_ncol = mat->ncol;
+        // check for temporal length of numerator alignments
+        if (static_cast<MatrixIndexT>(mpe->ref_ali.size()) != mat_nrow) {
+            KALDI_WARN << "Numerator alignment has wrong length "
+                << mpe->ref_ali.size() << " vs. "<< mat_nrow;
+            mpe->num_other_error++;
+            return 0;
+        }
+        if (mat_nrow > mpe->max_frames) {
+            KALDI_WARN << "Utterance " << utt << ": Skipped because it has " << mat_nrow <<
+                " frames, which is more than " << mpe->max_frames << ".";
+            mpe->num_other_error++;
+            return 0;
+        }
+        // 2) get the denominator lattice, preprocess
+        mpe->den_lat = mpe->den_lat_reader->Value(utt);
+        Lattice &den_lat = mpe->den_lat;
+        if (den_lat.Start() == -1) {
+            KALDI_WARN << "Empty lattice for utt " << utt;
+            mpe->num_other_error++;
+            return 0;
+        }
+        if (mpe->old_acoustic_scale != 1.0) {
+            fst::ScaleLattice(fst::AcousticLatticeScale(mpe->old_acoustic_scale),
+                    &den_lat);
+        }
+        // optional sort it topologically
+        kaldi::uint64 props = den_lat.Properties(fst::kFstProperties, false);
+        if (!(props & fst::kTopSorted)) {
+            if (fst::TopSort(&den_lat) == false)
+                KALDI_ERR << "Cycles detected in lattice.";
+        }
+        // get the lattice length and times of states
+        mpe->state_times.clear();
+        vector<int32> &state_times = mpe->state_times;
+        int32 max_time = kaldi::LatticeStateTimes(den_lat, &state_times);
+        // check for temporal length of denominator lattices
+        if (max_time != mat_nrow) {
+            KALDI_WARN << "Denominator lattice has wrong length "
+                << max_time << " vs. " << mat_nrow;
+            mpe->num_other_error++;
+            return 0;
+        }
+
+        return 1;
+    }
+
+    NervMatrix * calc_diff_mpe(KaldiMPE * mpe, NervMatrix * mat, const char * key)
+    {
+        std::string utt(key);
+        assert(sizeof(BaseFloat) == sizeof(float));
+
+        kaldi::Matrix<BaseFloat> nnet_out_h;
+        nnet_out_h.Resize(mat->nrow, mat->ncol, kUndefined);
+
+        size_t stride = mat->stride;
+        for (int i = 0; i < mat->nrow; i++)
+        {
+            const BaseFloat *nerv_row = (BaseFloat *)((char *)mat->data.f + i * stride);
+            BaseFloat *row = nnet_out_h.RowData(i);
+            memmove(row, nerv_row, sizeof(BaseFloat) * mat->ncol);
+        }
+
+        mpe->num_frames = nnet_out_h.NumRows();
+
+        PdfPriorOptions &prior_opts = *(mpe->prior_opts);
+        if (prior_opts.class_frame_counts != "") {
+            CuMatrix<BaseFloat> nnet_out;
+            nnet_out.Resize(mat->nrow, mat->ncol, kUndefined);
+            nnet_out.CopyFromMat(nnet_out_h);
+            mpe->log_prior->SubtractOnLogpost(&nnet_out);
+            nnet_out.Resize(0,0);
+        }
+
+        // 4) rescore the latice
+        LatticeAcousticRescore(nnet_out_h, *(mpe->trans_model), mpe->state_times, &(mpe->den_lat));
+        if (mpe->acoustic_scale != 1.0 || mpe->lm_scale != 1.0)
+            fst::ScaleLattice(fst::LatticeScale(mpe->lm_scale, mpe->acoustic_scale), &(mpe->den_lat));
+
+        kaldi::Posterior post;
+        std::vector<int32> &silence_phones = mpe->silence_phones;
+
+        if (mpe->do_smbr) {  // use state-level accuracies, i.e. sMBR estimation
+            mpe->utt_frame_acc = LatticeForwardBackwardMpeVariants(
+                    *(mpe->trans_model), silence_phones, mpe->den_lat, mpe->ref_ali, "smbr",
+                    mpe->one_silence_class, &post);
+        } else {  // use phone-level accuracies, i.e. MPFE (minimum phone frame error)
+            mpe->utt_frame_acc = LatticeForwardBackwardMpeVariants(
+                    *(mpe->trans_model), silence_phones, mpe->den_lat, mpe->ref_ali, "mpfe",
+                    mpe->one_silence_class, &post);
+        }
+
+        // 6) convert the Posterior to a matrix,
+        CuMatrix<BaseFloat> nnet_diff;
+        PosteriorToMatrixMapped(post, *(mpe->trans_model), &nnet_diff);
+        nnet_diff.Scale(-1.0); // need to flip the sign of derivative,
+
+        KALDI_VLOG(1) << "Lattice #" << mpe->num_done + 1 << " processed"
+            << " (" << utt << "): found " << mpe->den_lat.NumStates()
+            << " states and " << fst::NumArcs(mpe->den_lat) << " arcs.";
+
+        KALDI_VLOG(1) << "Utterance " << utt << ": Average frame accuracy = "
+            << (mpe->utt_frame_acc/mpe->num_frames) << " over " << mpe->num_frames
+            << " frames,"
+            << " diff-range(" << nnet_diff.Min() << "," << nnet_diff.Max() << ")";
+
+        nnet_diff.CopyToMat(&nnet_out_h);
+        nnet_diff.Resize(0,0); // release GPU memory,
+
+        assert(mat->nrow == nnet_out_h.NumRows() && mat->ncol == nnet_out_h.NumCols());
+        stride = mat->stride;
+        for (int i = 0; i < mat->nrow; i++)
+        {
+            const BaseFloat *row = nnet_out_h.RowData(i);
+            BaseFloat *nerv_row = (BaseFloat *)((char *)mat->data.f + i * stride);
+            memmove(nerv_row, row, sizeof(BaseFloat) * mat->ncol);
+        }
+        nnet_out_h.Resize(0,0);
+
+        // increase time counter
+        mpe->total_frame_acc += mpe->utt_frame_acc;
+        mpe->total_frames += mpe->num_frames;
+        mpe->num_done++;
+
+        if (mpe->num_done % 100 == 0) {
+            mpe->time_now = mpe->time->Elapsed();
+            KALDI_VLOG(1) << "After " << mpe->num_done << " utterances: time elapsed = "
+                << mpe->time_now/60 << " min; processed " << mpe->total_frames/mpe->time_now
+                << " frames per second.";
+#if HAVE_CUDA==1
+            // check the GPU is not overheated
+            CuDevice::Instantiate().CheckGpuHealth();
+#endif
+        }
+        return mat;
+    }
+
+    double get_num_frames_mpe(const KaldiMPE *mpe)
+    {
+        return (double)mpe->num_frames;
+    }
+
+    double get_utt_frame_acc_mpe(const KaldiMPE *mpe)
+    {
+        return (double)mpe->utt_frame_acc;
+    }
+
+}