adding dropout-by row

src/nnet3/nnet-chain-combine.cc

@@ -38,7 +38,7 @@ NnetChainCombiner::NnetChainCombiner(const NnetCombineConfig &combine_config,
     nnet_params_(std::min(num_nnets, combine_config_.max_effective_inputs),
                  NumParameters(first_nnet)),
     tot_input_weighting_(nnet_params_.NumRows()) {
-  SetDropoutProportion(0, &nnet_);
+  SetDropoutProportion(0, false, &nnet_);
   SubVector<BaseFloat> first_params(nnet_params_, 0);
   VectorizeNnet(nnet_, &first_params);
   tot_input_weighting_(0) += 1.0;

src/nnet3/nnet-combine.cc

@@ -34,7 +34,7 @@ NnetCombiner::NnetCombiner(const NnetCombineConfig &config,
     nnet_params_(std::min(num_nnets, config_.max_effective_inputs),
                  NumParameters(first_nnet)),
     tot_input_weighting_(nnet_params_.NumRows()) {
-  SetDropoutProportion(0, &nnet_);
+  SetDropoutProportion(0, false, &nnet_);
   SubVector<BaseFloat> first_params(nnet_params_, 0);
   VectorizeNnet(nnet_, &first_params);
   tot_input_weighting_(0) += 1.0;

src/nnet3/nnet-simple-component.cc

@@ -87,27 +87,39 @@ void PnormComponent::Write(std::ostream &os, bool binary) const {
 }
 
 
-void DropoutComponent::Init(int32 dim, BaseFloat dropout_proportion) {
+void DropoutComponent::Init(int32 dim, BaseFloat dropout_proportion, bool dropout_per_frame) {
   dropout_proportion_ = dropout_proportion;
+  dropout_per_frame_ = dropout_per_frame;
   dim_ = dim;
 }
 
 void DropoutComponent::InitFromConfig(ConfigLine *cfl) {
   int32 dim = 0;
   BaseFloat dropout_proportion = 0.0;
+  bool dropout_per_frame = false;
   bool ok = cfl->GetValue("dim", &dim) &&
     cfl->GetValue("dropout-proportion", &dropout_proportion);
+  bool ok2 = cfl->GetValue("dropout-per-frame", &dropout_per_frame);
   if (!ok || cfl->HasUnusedValues() || dim <= 0 ||
       dropout_proportion < 0.0 || dropout_proportion > 1.0)
     KALDI_ERR << "Invalid initializer for layer of type "
               << Type() << ": \"" << cfl->WholeLine() << "\"";
-  Init(dim, dropout_proportion);
+  if( ! ok2 )
+  {
+      dropout_per_frame = false;
+      Init(dim, dropout_proportion, dropout_per_frame);
+  }
+  else
+  {
+      Init(dim, dropout_proportion, dropout_per_frame);
+  }
 }
 
 std::string DropoutComponent::Info() const {
   std::ostringstream stream;
   stream << Type() << ", dim=" << dim_
-         << ", dropout-proportion=" << dropout_proportion_;
+         << ", dropout-proportion=" << dropout_proportion_
+         << ", dropout-per-frame=" << dropout_per_frame_;
   return stream.str();
 }
 
@@ -119,16 +131,36 @@ void DropoutComponent::Propagate(const ComponentPrecomputedIndexes *indexes,
 
   BaseFloat dropout = dropout_proportion_;
   KALDI_ASSERT(dropout >= 0.0 && dropout <= 1.0);
+  if(dropout_per_frame_ == true)
+  {
+    // This const_cast is only safe assuming you don't attempt
+    // to use multi-threaded code with the GPU.
+    const_cast<CuRand<BaseFloat>&>(random_generator_).RandUniform(out);
 
-  // This const_cast is only safe assuming you don't attempt
-  // to use multi-threaded code with the GPU.
-  const_cast<CuRand<BaseFloat>&>(random_generator_).RandUniform(out);
+    out->Add(-dropout); // now, a proportion "dropout" will be <0.0
+    out->ApplyHeaviside(); // apply the function (x>0?1:0).  Now, a proportion "dropout" will
+                          // be zero and (1 - dropout) will be 1.0.
 
-  out->Add(-dropout); // now, a proportion "dropout" will be <0.0
-  out->ApplyHeaviside(); // apply the function (x>0?1:0).  Now, a proportion "dropout" will
-                         // be zero and (1 - dropout) will be 1.0.
+    out->MulElements(in);
+  }
+  else
+  {
 
-  out->MulElements(in);
+    // This const_cast is only safe assuming you don't attempt
+    // to use multi-threaded code with the GPU.
+    const_cast<CuRand<BaseFloat>&>(random_generator_).RandUniform(out);
+    out->Add(-dropout); // now, a proportion "dropout" will be <0.0
+    out->ApplyHeaviside(); // apply the function (x>0?1:0).  Now, a proportion "dropout" will
+                           // be zero and (1 - dropout) will be 1.0.
+    CuVector<BaseFloat> *random_drop_vector = new CuVector<BaseFloat>(in.NumRows(), kSetZero);
+    MatrixIndexT i = 0;
+    random_drop_vector->CopyColFromMat(*out, i);
+    for (MatrixIndexT i = 0; i < in.NumCols(); i++)
+    {
+       out->CopyColFromVec(*random_drop_vector, i);
+    }
+    out->MulElements(in);
+  }
 }
 
 
@@ -154,6 +186,8 @@ void DropoutComponent::Read(std::istream &is, bool binary) {
   ReadBasicType(is, binary, &dim_);
   ExpectToken(is, binary, "<DropoutProportion>");
   ReadBasicType(is, binary, &dropout_proportion_);
+  ExpectToken(is, binary, "<DropoutPerFrame>");
+  ReadBasicType(is, binary, &dropout_per_frame_);
   ExpectToken(is, binary, "</DropoutComponent>");
 }
 
@@ -163,6 +197,8 @@ void DropoutComponent::Write(std::ostream &os, bool binary) const {
   WriteBasicType(os, binary, dim_);
   WriteToken(os, binary, "<DropoutProportion>");
   WriteBasicType(os, binary, dropout_proportion_);
+  WriteToken(os, binary, "<DropoutPerFrame>");
+  WriteBasicType(os, binary, dropout_per_frame_);
   WriteToken(os, binary, "</DropoutComponent>");
 }
 

src/nnet3/nnet-simple-component.h

@@ -87,11 +87,11 @@ class PnormComponent: public Component {
 // "Dropout: A Simple Way to Prevent Neural Networks from Overfitting".
 class DropoutComponent : public RandomComponent {
  public:
-  void Init(int32 dim, BaseFloat dropout_proportion = 0.0);
+  void Init(int32 dim, BaseFloat dropout_proportion = 0.0, bool dropout_per_frame = false);
 
-  DropoutComponent(int32 dim, BaseFloat dropout = 0.0) { Init(dim, dropout); }
+  DropoutComponent(int32 dim, BaseFloat dropout = 0.0, bool dropout_per_frame = false) { Init(dim, dropout, dropout_per_frame); }
 
-  DropoutComponent(): dim_(0), dropout_proportion_(0.0) { }
+  DropoutComponent(): dim_(0), dropout_proportion_(0.0), dropout_per_frame_(false) { }
 
   virtual int32 Properties() const {
     return kLinearInInput|kBackpropInPlace|kSimpleComponent|kBackpropNeedsInput|kBackpropNeedsOutput;
@@ -120,17 +120,21 @@ class DropoutComponent : public RandomComponent {
                         Component *to_update,
                         CuMatrixBase<BaseFloat> *in_deriv) const;
   virtual Component* Copy() const { return new DropoutComponent(dim_,
-                                                                dropout_proportion_); }
+                                                                dropout_proportion_,
+                                                                dropout_per_frame_); }
   virtual std::string Info() const;
 
-  void SetDropoutProportion(BaseFloat dropout_proportion) { dropout_proportion_ = dropout_proportion; }
+  void SetDropoutProportion(BaseFloat dropout_proportion, bool dropout_per_frame) {
+     dropout_proportion_ = dropout_proportion;
+     dropout_per_frame_ = dropout_per_frame;
+      }
 
  private:
   int32 dim_;
   /// dropout-proportion is the proportion that is dropped out,
   /// e.g. if 0.1, we set 10% to zero value.
   BaseFloat dropout_proportion_;
-
+  bool dropout_per_frame_;
 };
 
 class ElementwiseProductComponent: public Component {

src/nnet3/nnet-utils.cc

@@ -524,12 +524,14 @@ std::string NnetInfo(const Nnet &nnet) {
 }
 
 void SetDropoutProportion(BaseFloat dropout_proportion,
+                          bool dropout_per_frame ,
                           Nnet *nnet) {
+  dropout_per_frame = false;
   for (int32 c = 0; c < nnet->NumComponents(); c++) {
     Component *comp = nnet->GetComponent(c);
     DropoutComponent *dc = dynamic_cast<DropoutComponent*>(comp);
     if (dc != NULL)
-      dc->SetDropoutProportion(dropout_proportion);
+      dc->SetDropoutProportion(dropout_proportion, dropout_per_frame);
   }
 }
 
@@ -694,18 +696,22 @@ void ReadEditConfig(std::istream &edit_config_is, Nnet *nnet) {
       // matches names of components, not nodes.
       config_line.GetValue("name", &name_pattern);
       BaseFloat proportion = -1;
+      bool perframe = false;
       if (!config_line.GetValue("proportion", &proportion)) {
         KALDI_ERR << "In edits-config, expected proportion to be set in line: "
                   << config_line.WholeLine();
       }
+      if (!config_line.GetValue("perframe", &perframe)) {
+        perframe = false;
+      }
       DropoutComponent *component = NULL;
       int32 num_dropout_proportions_set = 0;
       for (int32 c = 0; c < nnet->NumComponents(); c++) {
         if (NameMatchesPattern(nnet->GetComponentName(c).c_str(),
                                name_pattern.c_str()) &&
             (component =
              dynamic_cast<DropoutComponent*>(nnet->GetComponent(c)))) {
-          component->SetDropoutProportion(proportion);
+          component->SetDropoutProportion(proportion, perframe);
           num_dropout_proportions_set++;
         }
       }

src/nnet3/nnet-utils.h

@@ -182,7 +182,7 @@ std::string NnetInfo(const Nnet &nnet);
 
 /// This function sets the dropout proportion in all dropout component to 
 /// dropout_proportion value.
-void SetDropoutProportion(BaseFloat dropout_proportion, Nnet *nnet);
+void SetDropoutProportion(BaseFloat dropout_proportion, bool dropout_per_frame, Nnet *nnet);
 
 /// This function finds a list of components that are never used, and outputs
 /// the integer comopnent indexes (you can use these to index
@@ -233,7 +233,7 @@ void FindOrphanNodes(const Nnet &nnet, std::vector<int32> *nodes);
        remove internal nodes directly; instead you should use the command
        'remove-orphans'.
 
-    set-dropout-proportion [name=<name-pattern>] proportion=<dropout-proportion>
+    set-dropout-proportion [name=<name-pattern>] proportion=<dropout-proportion> perframe=<perframe>
        Sets the dropout rates for any components of type DropoutComponent whose
        names match the given <name-pattern> (e.g. lstm*).  <name-pattern> defaults to "*".
    \endverbatim

src/nnet3bin/nnet3-combine.cc

@@ -104,7 +104,7 @@ int main(int argc, char *argv[]) {
     } else {
       KALDI_LOG << "Copying the single input model directly to the output, "
                 << "without any combination.";
-      SetDropoutProportion(0, &nnet);
+      SetDropoutProportion(0, false, &nnet);
       WriteKaldiObject(nnet, nnet_wxfilename, binary_write);
     } 
     KALDI_LOG << "Finished combining neural nets, wrote model to "