Preparing code to move into kaldi repository.

Fixing stuff and renaming into am_nnet.

src/nnet3/Makefile

@@ -28,7 +28,7 @@ OBJFILES = nnet-common.o nnet-compile.o nnet-component-itf.o \
 	discriminative-supervision.o nnet-discriminative-example.o \
 	nnet-discriminative-diagnostics.o \
 	discriminative-training.o nnet-discriminative-training.o \
-	online-nnet3-decodable.o
+	online-nnet3-decodable-simple.o
 
 
 LIBNAME = kaldi-nnet3

src/nnet3/online-nnet3-decodable.cc → src/nnet3/online-nnet3-decodable-simple.cc

@@ -18,37 +18,37 @@
 // See the Apache 2 License for the specific language governing permissions and
 // limitations under the License.
 
-#include "nnet3/online-nnet3-decodable.h"
+#include <nnet3/online-nnet3-decodable-simple.h>
 #include "nnet3/nnet-utils.h"
 
 namespace kaldi {
 namespace nnet3 {
 
-DecodableNnet3Online::DecodableNnet3Online(
-    const AmNnetSimple &nnet,
+DecodableNnet3SimpleOnline::DecodableNnet3SimpleOnline(
+    const AmNnetSimple &am_nnet,
     const TransitionModel &trans_model,
     const DecodableNnet3OnlineOptions &opts,
     OnlineFeatureInterface *input_feats):
-    compiler_(nnet.GetNnet(), opts.optimize_config),
+    compiler_(am_nnet.GetNnet(), opts.optimize_config),
     features_(input_feats),
-    nnet_(nnet),
+    am_nnet_(am_nnet),
     trans_model_(trans_model),
     opts_(opts),
     feat_dim_(input_feats->Dim()),
-    num_pdfs_(nnet.GetNnet().OutputDim("output")),
+    num_pdfs_(am_nnet.GetNnet().OutputDim("output")),
     begin_frame_(-1) {
   KALDI_ASSERT(opts_.max_nnet_batch_size > 0);
-  log_priors_ = nnet_.Priors();
+  log_priors_ = am_nnet_.Priors();
   KALDI_ASSERT((log_priors_.Dim() == 0 || log_priors_.Dim() == trans_model_.NumPdfs()) &&
                "Priors in neural network must match with transition model (if exist).");
 
-  ComputeSimpleNnetContext(nnet_.GetNnet(), &left_context_, &right_context_);
+  ComputeSimpleNnetContext(am_nnet_.GetNnet(), &left_context_, &right_context_);
   log_priors_.ApplyLog();
 }
 
 
 
-BaseFloat DecodableNnet3Online::LogLikelihood(int32 frame, int32 index) {
+BaseFloat DecodableNnet3SimpleOnline::LogLikelihood(int32 frame, int32 index) {
   ComputeForFrame(frame);
   int32 pdf_id = trans_model_.TransitionIdToPdf(index);
   KALDI_ASSERT(frame >= begin_frame_ &&
@@ -57,31 +57,31 @@ BaseFloat DecodableNnet3Online::LogLikelihood(int32 frame, int32 index) {
 }
 
 
-bool DecodableNnet3Online::IsLastFrame(int32 frame) const {
+bool DecodableNnet3SimpleOnline::IsLastFrame(int32 frame) const {
   KALDI_ASSERT(false && "Method is not imlemented");
   return false;
 }
 
-int32 DecodableNnet3Online::NumFramesReady() const {
+int32 DecodableNnet3SimpleOnline::NumFramesReady() const {
   int32 features_ready = features_->NumFramesReady();
   if (features_ready == 0)
     return 0;
   bool input_finished = features_->IsLastFrame(features_ready - 1);
   if (opts_.pad_input) {
     // normal case... we'll pad with duplicates of first + last frame to get the
     // required left and right context.
-    if (input_finished) return subsampling(features_ready);
-    else return std::max<int32>(0, subsampling(features_ready - right_context_));
+    if (input_finished) return NumSubsampledFrames(features_ready);
+    else return std::max<int32>(0, NumSubsampledFrames(features_ready - right_context_));
   } else {
-    return std::max<int32>(0, subsampling(features_ready - right_context_ - left_context_));
+    return std::max<int32>(0, NumSubsampledFrames(features_ready - right_context_ - left_context_));
   }
 }
 
-int32 DecodableNnet3Online::subsampling(int32 num_frames) const {
+int32 DecodableNnet3SimpleOnline::NumSubsampledFrames(int32 num_frames) const {
   return (num_frames) / opts_.frame_subsampling_factor;
 }
 
-void DecodableNnet3Online::ComputeForFrame(int32 subsampled_frame) {
+void DecodableNnet3SimpleOnline::ComputeForFrame(int32 subsampled_frame) {
   int32 features_ready = features_->NumFramesReady();
   bool input_finished = features_->IsLastFrame(features_ready - 1);  
   KALDI_ASSERT(subsampled_frame >= 0);
@@ -118,13 +118,13 @@ void DecodableNnet3Online::ComputeForFrame(int32 subsampled_frame) {
     features_->GetFrame(t_modified, &row);
   }
 
-  int32 num_subsampled_frames = subsampling(input_frame_end - input_frame_begin -
+  int32 num_subsampled_frames = NumSubsampledFrames(input_frame_end - input_frame_begin -
           left_context_ - right_context_);
   // I'm not checking if the input feature vector is ok.
   // It should be done, but I'm not sure if it is the best place. 
   // Maybe a new "nnet3 feature pipeline"?
-  int32 mfcc_dim = nnet_.GetNnet().InputDim("input");
-  int32 ivector_dim = nnet_.GetNnet().InputDim("ivector");
+  int32 mfcc_dim = am_nnet_.GetNnet().InputDim("input");
+  int32 ivector_dim = am_nnet_.GetNnet().InputDim("ivector");
   // MFCCs in the left chunk
   SubMatrix<BaseFloat> mfcc_mat = features.ColRange(0,mfcc_dim);
 
@@ -143,7 +143,7 @@ void DecodableNnet3Online::ComputeForFrame(int32 subsampled_frame) {
   begin_frame_ = subsampled_frame;
 }
 
-void DecodableNnet3Online::DoNnetComputation(
+void DecodableNnet3SimpleOnline::DoNnetComputation(
     int32 input_t_start,
     const MatrixBase<BaseFloat> &input_feats,
     const VectorBase<BaseFloat> &ivector,
@@ -182,7 +182,7 @@ void DecodableNnet3Online::DoNnetComputation(
   const NnetComputation *computation = compiler_.Compile(request);
   Nnet *nnet_to_update = NULL;  // we're not doing any update.
   NnetComputer computer(opts_.compute_config, *computation,
-                        nnet_.GetNnet(), nnet_to_update);
+                        am_nnet_.GetNnet(), nnet_to_update);
 
   CuMatrix<BaseFloat> input_feats_cu(input_feats);
   computer.AcceptInput("input", &input_feats_cu);

src/nnet3/online-nnet3-decodable.h → src/nnet3/online-nnet3-decodable-simple.h

@@ -1,4 +1,4 @@
-// nnet3/online-nnet3-decodable.h
+// nnet3/online-nnet3-decodable-simple.h
 
 // Copyright  2014  Johns Hopkins Universithy (author: Daniel Povey)
 //            2016  Api.ai (Author: Ilya Platonov)
@@ -62,9 +62,9 @@ struct DecodableNnet3OnlineOptions {
                    "frames (this will rarely make a difference)");
 
     opts->Register("frame-subsampling-factor", &frame_subsampling_factor,
-                       "Required if the frame-rate of the output (e.g. in 'chain' "
-                       "models) is less than the frame-rate of the original "
-                       "alignment.");
+                   "Required if the frame-rate of the output (e.g. in 'chain' "
+                   "models) is less than the frame-rate of the original "
+                   "alignment.");
 
     // register the optimization options with the prefix "optimization".
     ParseOptions optimization_opts("optimization", opts);
@@ -84,9 +84,9 @@ struct DecodableNnet3OnlineOptions {
    feature input from a matrix.
 */
 
-class DecodableNnet3Online: public DecodableInterface {
+class DecodableNnet3SimpleOnline: public DecodableInterface {
  public:
-  DecodableNnet3Online(const AmNnetSimple &nnet,
+  DecodableNnet3SimpleOnline(const AmNnetSimple &am_nnet,
                        const TransitionModel &trans_model,
                        const DecodableNnet3OnlineOptions &opts,
                        OnlineFeatureInterface *input_feats);
@@ -108,7 +108,7 @@ class DecodableNnet3Online: public DecodableInterface {
   /// them (and possibly for some succeeding frames)
   void ComputeForFrame(int32 frame);
   // corrects number of frames by frame_subsampling_factor;
-  int32 subsampling(int32) const;
+  int32 NumSubsampledFrames(int32) const;
 
   void DoNnetComputation(
       int32 input_t_start,
@@ -120,7 +120,7 @@ class DecodableNnet3Online: public DecodableInterface {
   CachingOptimizingCompiler compiler_;
 
   OnlineFeatureInterface *features_;
-  const AmNnetSimple &nnet_;
+  const AmNnetSimple &am_nnet_;
   const TransitionModel &trans_model_;
   DecodableNnet3OnlineOptions opts_;
   CuVector<BaseFloat> log_priors_;  // log-priors taken from the model.
@@ -143,7 +143,7 @@ class DecodableNnet3Online: public DecodableInterface {
   // opts_.max_nnet_batch_size.
   Matrix<BaseFloat> scaled_loglikes_;
 
-  KALDI_DISALLOW_COPY_AND_ASSIGN(DecodableNnet3Online);
+  KALDI_DISALLOW_COPY_AND_ASSIGN(DecodableNnet3SimpleOnline);
 };
 
 } // namespace nnet3

src/online2/online-nnet3-decoding.cc

@@ -27,13 +27,13 @@ namespace kaldi {
 SingleUtteranceNnet3Decoder::SingleUtteranceNnet3Decoder(
     const OnlineNnet3DecodingConfig &config,
     const TransitionModel &tmodel,
-    const nnet3::AmNnetSimple &model,
+    const nnet3::AmNnetSimple &am_model,
     const fst::Fst<fst::StdArc> &fst,
     OnlineNnet2FeaturePipeline *feature_pipeline):
     config_(config),
     feature_pipeline_(feature_pipeline),
     tmodel_(tmodel),
-    decodable_(model, tmodel, config.decodable_opts, feature_pipeline),
+    decodable_(am_model, tmodel, config.decodable_opts, feature_pipeline),
     decoder_(fst, config.decoder_opts) {
   decoder_.InitDecoding();
 }

src/online2/online-nnet3-decoding.h

@@ -26,10 +26,10 @@
 #include <vector>
 #include <deque>
 
+#include "../nnet3/online-nnet3-decodable-simple.h"
 #include "matrix/matrix-lib.h"
 #include "util/common-utils.h"
 #include "base/kaldi-error.h"
-#include "nnet3/online-nnet3-decodable.h"
 #include "online2/online-nnet2-feature-pipeline.h"
 #include "online2/online-endpoint.h"
 #include "decoder/lattice-faster-online-decoder.h"
@@ -71,7 +71,7 @@ class SingleUtteranceNnet3Decoder {
   // class, it's owned externally.
   SingleUtteranceNnet3Decoder(const OnlineNnet3DecodingConfig &config,
                               const TransitionModel &tmodel,
-                              const nnet3::AmNnetSimple &model,
+                              const nnet3::AmNnetSimple &am_model,
                               const fst::Fst<fst::StdArc> &fst,
                               OnlineNnet2FeaturePipeline *feature_pipeline);
 
@@ -116,7 +116,7 @@ class SingleUtteranceNnet3Decoder {
 
   const TransitionModel &tmodel_;
 
-  nnet3::DecodableNnet3Online decodable_;
+  nnet3::DecodableNnet3SimpleOnline decodable_;
 
   LatticeFasterOnlineDecoder decoder_;
 

src/online2bin/online2-wav-nnet3-latgen-faster.cc

@@ -151,12 +151,12 @@ int main(int argc, char *argv[]) {
     }
 
     TransitionModel trans_model;
-    nnet3::AmNnetSimple nnet;
+    nnet3::AmNnetSimple am_nnet;
     {
       bool binary;
       Input ki(nnet3_rxfilename, &binary);
       trans_model.Read(ki.Stream(), binary);
-      nnet.Read(ki.Stream(), binary);
+      am_nnet.Read(ki.Stream(), binary);
     }
 
     fst::Fst<fst::StdArc> *decode_fst = ReadFstKaldi(fst_rxfilename);
@@ -203,7 +203,7 @@ int main(int argc, char *argv[]) {
 
         SingleUtteranceNnet3Decoder decoder(nnet3_decoding_config,
                                             trans_model,
-                                            nnet,
+                                            am_nnet,
                                             *decode_fst,
                                             &feature_pipeline);
         OnlineTimer decoding_timer(utt);