Merge pull request #4902 from dzen03/fix-unused-variable

Fix unused but set variable

src/base/kaldi-error.h

@@ -185,25 +185,25 @@ class MessageLogger {
 #define KALDI_ASSERT(cond)                                                     \
   do {                                                                         \
     if (cond)                                                                  \
-      (void)0;                                                                 \
+      (void)(cond);                                                            \
     else                                                                       \
       ::kaldi::KaldiAssertFailure_(__func__, __FILE__, __LINE__, #cond);       \
   } while (0)
 #else
-#define KALDI_ASSERT(cond) (void)0
+#define KALDI_ASSERT(cond) (void)(cond)
 #endif
 
 // Some more expensive asserts only checked if this defined.
 #ifdef KALDI_PARANOID
 #define KALDI_PARANOID_ASSERT(cond)                                            \
   do {                                                                         \
     if (cond)                                                                  \
-      (void)0;                                                                 \
+      (void)(cond);                                                            \
     else                                                                       \
       ::kaldi::KaldiAssertFailure_(__func__, __FILE__, __LINE__, #cond);       \
   } while (0)
 #else
-#define KALDI_PARANOID_ASSERT(cond) (void)0
+#define KALDI_PARANOID_ASSERT(cond) (void)(cond)
 #endif
 
 /***** THIRD-PARTY LOG-HANDLER *****/

src/bin/matrix-sum.cc

@@ -49,7 +49,7 @@ int32 TypeOneUsage(const ParseOptions &po,
   }
 
   int32 n_utts = 0, n_total_matrices = 0,
-      n_success = 0, n_missing = 0, n_other_errors = 0;
+      n_success = 0, n_missing = 0;
 
   for (; !matrix_reader1.Done(); matrix_reader1.Next()) {
     std::string key = matrix_reader1.Key();
@@ -78,7 +78,6 @@ int32 TypeOneUsage(const ParseOptions &po,
                      << matrix_in_fns[i] << " vs " << matrix_out.NumRows()
                      << " by " << matrix_out.NumCols()
                      << " primary matrix, rspecifier:" << matrix_in_fn1;
-          n_other_errors++;
         }
       } else {
         KALDI_WARN << "No matrix found for utterance " << key << " for "
@@ -124,7 +123,7 @@ int32 TypeOneUsageAverage(const ParseOptions &po) {
   }
 
   int32 n_utts = 0, n_total_matrices = 0,
-      n_success = 0, n_missing = 0, n_other_errors = 0;
+      n_success = 0, n_missing = 0;
 
   for (; !matrix_reader1.Done(); matrix_reader1.Next()) {
     std::string key = matrix_reader1.Key();
@@ -151,7 +150,6 @@ int32 TypeOneUsageAverage(const ParseOptions &po) {
                      << matrix_in_fns[i] << " vs " << matrix_out.NumRows()
                      << " by " << matrix_out.NumCols()
                      << " primary matrix, rspecifier:" << matrix_in_fn1;
-          n_other_errors++;
         }
       } else {
         KALDI_WARN << "No matrix found for utterance " << key << " for "

src/bin/vector-sum.cc

@@ -52,7 +52,7 @@ int32 TypeOneUsage(const ParseOptions &po) {
   }
 
   int32 n_utts = 0, n_total_vectors = 0,
-      n_success = 0, n_missing = 0, n_other_errors = 0;
+      n_success = 0, n_missing = 0;
 
   for (; !vector_reader1.Done(); vector_reader1.Next()) {
     std::string key = vector_reader1.Key();
@@ -75,7 +75,6 @@ int32 TypeOneUsage(const ParseOptions &po) {
                      << "system " << (i + 2) << ", rspecifier: "
                      << vector_in_fns[i] << " vs " << vector_out.Dim()
                      << " primary vector, rspecifier:" << vector_in_fn1;
-          n_other_errors++;
         }
       } else {
         KALDI_WARN << "No vector found for utterance " << key << " for "

src/chainbin/nnet3-chain-copy-egs.cc

@@ -347,7 +347,7 @@ int main(int argc, char *argv[]) {
                                             // not configurable for now.
     exclude_names.push_back(std::string("ivector"));
 
-    int64 num_read = 0, num_written = 0, num_err = 0;
+    int64 num_read = 0, num_written = 0;
     for (; !example_reader.Done(); example_reader.Next(), num_read++) {
       const std::string &key = example_reader.Key();
       NnetChainExample &eg = example_reader.Value();
@@ -361,7 +361,6 @@ int main(int argc, char *argv[]) {
         BaseFloat weight = 1.0;
         if (!egs_weight_reader.HasKey(key)) {
           KALDI_WARN << "No weight for example key " << key;
-          num_err++;
           continue;
         }
         weight = egs_weight_reader.Value(key);
@@ -371,7 +370,6 @@ int main(int argc, char *argv[]) {
       if (!eg_output_name_rspecifier.empty()) {
         if (!output_name_reader.HasKey(key)) {
           KALDI_WARN << "No new output-name for example key " << key;
-          num_err++;
           continue;
         }
         std::string new_output_name = output_name_reader.Value(key);

src/fstext/pre-determinize-inl.h

@@ -411,8 +411,6 @@ void PreDeterminize(MutableFst<Arc> *fst,
   std::vector<bool> d_vec(max_state+1, false);  // "done vector".  Purely for debugging.
 
 
-  size_t num_extra_det_states = 0;
-
   // (D)(v)
   while (Q.size() != 0) {
 
@@ -491,7 +489,6 @@ void PreDeterminize(MutableFst<Arc> *fst,
                 assert(m_map.count(this_pr.first) == 0);
                 m_map[this_pr.first] = k;
                 k++;
-                num_extra_det_states++;
               }
             } else {  // Create the set V_t.
               V_t.insert(this_pr.second);

src/gmm/mle-diag-gmm-test.cc

@@ -139,12 +139,10 @@ void test_flags_driven_update(const DiagGmm &gmm,
 
   // now both models gmm_all_update, gmm_all_update have the same params updated
   // compute loglike for models for check
-  double loglike0 = 0.0;
   double loglike1 = 0.0;
   double loglike2 = 0.0;
   for (int32 i = 0; i < feats.NumRows(); i++) {
-    loglike0 += static_cast<double>(
-      gmm.LogLikelihood(feats.Row(i)));
+    gmm.LogLikelihood(feats.Row(i));
     loglike1 += static_cast<double>(
       gmm_all_update.LogLikelihood(feats.Row(i)));
     loglike2 += static_cast<double>(
@@ -366,9 +364,8 @@ UnitTestEstimateDiagGmm() {
     est_gmm.Resize(gmm->NumGauss(),
       gmm->Dim(), flags_all);
     est_gmm.SetZero(flags_all);
-    float loglike = 0.0;
     for (size_t i = 0; i < counter; i++) {
-      loglike += est_gmm.AccumulateFromDiag(*gmm, feats.Row(i), 1.0F);
+      est_gmm.AccumulateFromDiag(*gmm, feats.Row(i), 1.0F);
     }
     test_io(*gmm, est_gmm, false, feats);  // ASCII mode
     test_io(*gmm, est_gmm, true, feats);   // Binary mode

src/gmm/mle-full-gmm-test.cc

@@ -200,12 +200,10 @@ void test_flags_driven_update(const FullGmm &gmm,
 
   // now both models gmm_all_update, gmm_all_update have the same params updated
   // compute loglike for models for check
-  double loglike0 = 0.0;
   double loglike1 = 0.0;
   double loglike2 = 0.0;
   for (int32 i = 0; i < feats.NumRows(); i++) {
-    loglike0 += static_cast<double>(
-      gmm.LogLikelihood(feats.Row(i)));
+    gmm.LogLikelihood(feats.Row(i));
     loglike1 += static_cast<double>(
       gmm_all_update.LogLikelihood(feats.Row(i)));
     loglike2 += static_cast<double>(
@@ -462,9 +460,8 @@ UnitTestEstimateFullGmm() {
     est_gmm.Resize(gmm->NumGauss(),
       gmm->Dim(), flags_all);
     est_gmm.SetZero(flags_all);
-    float loglike = 0.0;
     for (int32 i = 0; i < counter; i++) {
-      loglike += est_gmm.AccumulateFromFull(*gmm, feats.Row(i), 1.0F);
+      est_gmm.AccumulateFromFull(*gmm, feats.Row(i), 1.0F);
     }
     test_io(*gmm, est_gmm, false, feats);
     test_io(*gmm, est_gmm, true, feats);

src/gmmbin/gmm-acc-mllt-global.cc

@@ -72,7 +72,7 @@ int main(int argc, char *argv[]) {
     SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier);
     RandomAccessInt32VectorVectorReader gselect_reader(gselect_rspecifier);
 
-    int32 num_done = 0, num_err = 0;
+    int32 num_done = 0;
     for (; !feature_reader.Done(); feature_reader.Next()) {
       std::string utt = feature_reader.Key();
       const Matrix<BaseFloat> &mat = feature_reader.Value();      
@@ -88,15 +88,13 @@ int main(int argc, char *argv[]) {
       } else {
         if (!gselect_reader.HasKey(utt)) {
           KALDI_WARN << "No gselect information for utterance " << utt;
-          num_err++;
           continue;
         }
         const std::vector<std::vector<int32> > &gselect= gselect_reader.Value(utt);
         if (static_cast<int32>(gselect.size()) != mat.NumRows()) {
           KALDI_WARN << "Gselect information has wrong size for utterance "
                      << utt << ", " << gselect.size() << " vs. "
                      << mat.NumRows();
-          num_err++;
           continue;
         }
 

src/ivector/ivector-extractor-test.cc

@@ -94,11 +94,10 @@ void TestIvectorExtraction(const IvectorExtractor &extractor,
       ivector_dim = extractor.IvectorDim();
   Posterior post(num_frames);
 
-  double tot_log_like = 0.0;
   for (int32 t = 0; t < num_frames; t++) {
     SubVector<BaseFloat> frame(feats, t);
     Vector<BaseFloat> posterior(fgmm.NumGauss(), kUndefined);
-    tot_log_like += fgmm.ComponentPosteriors(frame, &posterior);
+    fgmm.ComponentPosteriors(frame, &posterior);
     for (int32 i = 0; i < posterior.Dim(); i++)
       post[t].push_back(std::make_pair(i, posterior(i)));
   }

src/kwsbin/kws-search.cc

@@ -287,7 +287,6 @@ int main(int argc, char *argv[]) {
     ArcSort(&index, fst::ILabelCompare<KwsLexicographicArc>());
 
     int32 n_done = 0;
-    int32 n_fail = 0;
     for (; !keyword_reader.Done(); keyword_reader.Next()) {
       std::string key = keyword_reader.Key();
       VectorFst<StdArc> keyword = keyword_reader.Value();
@@ -336,7 +335,6 @@ int main(int argc, char *argv[]) {
         if (result_fst.Final(arc.nextstate) != Weight::One()) {
           KALDI_WARN << "The resulting FST does not have "
                      << "the expected structure for key " << key;
-          n_fail++;
           continue;
         }
 

src/latbin/lattice-oracle.cc

@@ -257,7 +257,7 @@ int main(int argc, char *argv[]) {
     }
 
     int32 n_done = 0, n_fail = 0;
-    int32 tot_correct = 0, tot_substitutions = 0,
+    int32 tot_substitutions = 0,
           tot_insertions = 0, tot_deletions = 0, tot_words = 0;
 
     for (; !lattice_reader.Done(); lattice_reader.Next()) {
@@ -320,7 +320,6 @@ int main(int argc, char *argv[]) {
         KALDI_LOG << "%WER " << (100.*tot_errs) / num_words << " [ " << tot_errs
                   << " / " << num_words << ", " << insertions << " insertions, "
                   << deletions << " deletions, " << substitutions << " sub ]";
-        tot_correct += correct;
         tot_substitutions += substitutions;
         tot_insertions += insertions;
         tot_deletions += deletions;

src/latbin/lattice-prune.cc

@@ -68,7 +68,7 @@ int main(int argc, char *argv[]) {
     SequentialCompactLatticeReader compact_lattice_reader(lats_rspecifier);
     CompactLatticeWriter compact_lattice_writer(lats_wspecifier); 
 
-    int32 n_done = 0, n_err = 0;
+    int32 n_done = 0;
     int64 n_arcs_in = 0, n_arcs_out = 0,
         n_states_in = 0, n_states_out = 0;
 
@@ -86,7 +86,6 @@ int main(int argc, char *argv[]) {
       CompactLattice pruned_clat(clat);
       if (!PruneLattice(beam, &pruned_clat)) {
         KALDI_WARN << "Error pruning lattice for utterance " << key;
-        n_err++;
       }
       int64 pruned_narcs = NumArcs(pruned_clat),          
           pruned_nstates = pruned_clat.NumStates();

src/latbin/lattice-to-mpe-post.cc

@@ -94,7 +94,7 @@ int main(int argc, char *argv[]) {
       trans_model.Read(ki.Stream(), binary);
     }
 
-    int32 num_done = 0, num_err = 0;
+    int32 num_done = 0;
     double total_lat_frame_acc = 0.0, lat_frame_acc;
     double total_time = 0, lat_time;
 
@@ -114,7 +114,6 @@ int main(int argc, char *argv[]) {
 
       if (!alignments_reader.HasKey(key)) {
         KALDI_WARN << "No alignment for utterance " << key;
-        num_err++;
       } else {
         const std::vector<int32> &alignment = alignments_reader.Value(key);
         Posterior post;

src/latbin/lattice-to-smbr-post.cc

@@ -95,7 +95,7 @@ int main(int argc, char *argv[]) {
       trans_model.Read(ki.Stream(), binary);
     }
 
-    int32 num_done = 0, num_err = 0;
+    int32 num_done = 0;
     double total_lat_frame_acc = 0.0, lat_frame_acc;
     double total_time = 0, lat_time;
 
@@ -115,7 +115,6 @@ int main(int argc, char *argv[]) {
 
       if (!alignments_reader.HasKey(key)) {
         KALDI_WARN << "No alignment for utterance " << key;
-        num_err++;
       } else {
         const std::vector<int32> &alignment = alignments_reader.Value(key);
         Posterior post;

src/matrix/matrix-functions.cc

@@ -669,12 +669,10 @@ void ComputePca(const MatrixBase<Real> &X,
       Nsp.TopEigs(&l, &Vtmp);
     }
 
-    MatrixIndexT num_zeroed = 0;
     for (MatrixIndexT g = 0; g < G; g++) {
       if (l(g) < 0.0) {
         KALDI_WARN << "In PCA, setting element " << l(g) << " to zero.";
         l(g) = 0.0;
-        num_zeroed++;
       }
     }
     SortSvd(&l, &Vtmp); // Make sure zero elements are last, this

src/nnet2/nnet-compute-discriminative.cc

@@ -296,15 +296,14 @@ void NnetDiscriminativeUpdater::LatticeComputations() {
 
   ScalePosterior(eg_.weight, &post);
 
-  double tot_num_post = 0.0, tot_den_post = 0.0;
+  double tot_num_post = 0.0;
   std::vector<MatrixElement<BaseFloat> > sv_labels;
   sv_labels.reserve(answers.size());
   for (int32 t = 0; t < post.size(); t++) {
     for (int32 i = 0; i < post[t].size(); i++) {
       int32 pdf_id = post[t][i].first;
       BaseFloat weight = post[t][i].second;
       if (weight > 0.0) { tot_num_post += weight; }
-      else { tot_den_post -= weight; }
       MatrixElement<BaseFloat> elem = {t, pdf_id, weight};
       sv_labels.push_back(elem);
     }

src/nnet3/nnet-example-utils.cc

@@ -673,11 +673,9 @@ void UtteranceSplitter::InitSplits(std::vector<std::vector<int32> > *splits) con
         vec.push_back(config_.num_frames[i]);
       if (j > 0)
         vec.push_back(config_.num_frames[j]);
-      int32 n = 0;
       while (DefaultDurationOfSplit(vec) <= default_duration_ceiling) {
         if (!vec.empty()) // Don't allow the empty vector as a split.
           splits_set.insert(vec);
-        n++;
         vec.push_back(primary_length);
         std::sort(vec.begin(), vec.end());
       }

src/online2bin/apply-cmvn-online.cc

@@ -68,7 +68,7 @@ int main(int argc, char *argv[]) {
 
 
     BaseFloatMatrixWriter feature_writer(feature_wspecifier);
-    int32 num_done = 0, num_err = 0;
+    int32 num_done = 0;
     int64 tot_t = 0;
 
     if (spk2utt_rspecifier != "") {
@@ -82,7 +82,6 @@ int main(int argc, char *argv[]) {
           std::string utt = uttlist[i];
           if (!feature_reader.HasKey(utt)) {
             KALDI_WARN << "No features for utterance " << utt;
-            num_err++;
             continue;
           }
           const Matrix<BaseFloat> &feats = feature_reader.Value(utt);

src/online2bin/ivector-extract-online2.cc

@@ -82,7 +82,7 @@ int main(int argc, char *argv[]) {
         feature_rspecifier = po.GetArg(2),
         ivectors_wspecifier = po.GetArg(3);
 
-    double tot_ubm_loglike = 0.0, tot_objf_impr = 0.0, tot_t = 0.0,
+    double tot_objf_impr = 0.0, tot_t = 0.0,
         tot_length = 0.0, tot_length_utt_end = 0.0;
     int32 num_done = 0, num_err = 0;
 
@@ -166,7 +166,6 @@ int main(int argc, char *argv[]) {
         }
         // Update diagnostics.
 
-        tot_ubm_loglike += T * ivector_feature.UbmLogLikePerFrame();
         tot_objf_impr += T * ivector_feature.ObjfImprPerFrame();
         tot_length_utt_end += T * ivectors.Row(num_ivectors - 1).Norm(2.0);
         for (int32 i = 0; i < num_ivectors; i++)

src/tree/build-tree-utils.cc

@@ -538,7 +538,6 @@ EventMap *SplitDecisionTree(const EventMap &input_map,
                             BaseFloat *obj_impr_out,
                             BaseFloat *smallest_split_change_out) {
   KALDI_ASSERT(num_leaves != NULL && *num_leaves > 0);  // can't be 0 or input_map would be empty.
-  int32 num_empty_leaves = 0;
   BaseFloat like_impr = 0.0;
   BaseFloat smallest_split_change = 1.0e+20;
   std::vector<DecisionTreeSplitter*> builders;
@@ -550,7 +549,6 @@ EventMap *SplitDecisionTree(const EventMap &input_map,
     builders.resize(split_stats.size());  // size == #leaves.
     for (size_t i = 0;i < split_stats.size();i++) {
       EventAnswerType leaf = static_cast<EventAnswerType>(i);
-      if (split_stats[i].size() == 0) num_empty_leaves++;
       builders[i] = new DecisionTreeSplitter(leaf, split_stats[i], q_opts);
     }
   }