diff --git a/src/nnet3/nnet-attention-component.cc b/src/nnet3/nnet-attention-component.cc
index 758f5673f33..3d7fb649603 100644
--- a/src/nnet3/nnet-attention-component.cc
+++ b/src/nnet3/nnet-attention-component.cc
@@ -33,6 +33,7 @@ std::string RestrictedAttentionComponent::Info() const {
   stream << Type() << ", input-dim=" << InputDim()
          << ", output-dim=" << OutputDim()
          << ", num-heads=" << num_heads_
+         << ", time-stride=" << time_stride_
          << ", key-dim=" << key_dim_
          << ", value-dim=" << value_dim_
          << ", num-left-inputs=" << num_left_inputs_
@@ -486,7 +487,7 @@ void RestrictedAttentionComponent::GetInputIndexes(
   desired_indexes->resize(context_dim_);
   int32 n = output_index.n, x = output_index.x,
       i = 0;
-  for (int32 t = first_time, i = 0; t <= last_time; t += time_stride_, i++) {
+  for (int32 t = first_time; t <= last_time; t += time_stride_, i++) {
     (*desired_indexes)[i].n = n;
     (*desired_indexes)[i].t = t;
     (*desired_indexes)[i].x = x;
diff --git a/src/nnet3/nnet-component-itf.cc b/src/nnet3/nnet-component-itf.cc
index d462ce890d4..5f1052efc81 100644
--- a/src/nnet3/nnet-component-itf.cc
+++ b/src/nnet3/nnet-component-itf.cc
@@ -25,10 +25,12 @@
 #include "nnet3/nnet-simple-component.h"
 #include "nnet3/nnet-general-component.h"
 #include "nnet3/nnet-convolutional-component.h"
+#include "nnet3/nnet-attention-component.h"
 #include "nnet3/nnet-parse.h"
 #include "nnet3/nnet-computation-graph.h"
 
 
+
 // \file This file contains some more-generic component code: things in base classes.
 //       See nnet-component.cc for the code of the actual Components.
 
@@ -61,6 +63,8 @@ ComponentPrecomputedIndexes* ComponentPrecomputedIndexes::NewComponentPrecompute
     ans = new BackpropTruncationComponentPrecomputedIndexes();
   } else if (cpi_type == "TimeHeightConvolutionComponentPrecomputedIndexes") {
     ans = new TimeHeightConvolutionComponent::PrecomputedIndexes();
+  } else if (cpi_type == "RestrictedAttentionComponentPrecomputedIndexes") {
+    ans = new RestrictedAttentionComponent::PrecomputedIndexes();
   }
   if (ans != NULL) {
     KALDI_ASSERT(cpi_type == ans->Type());
@@ -159,6 +163,8 @@ Component* Component::NewComponentOfType(const std::string &component_type) {
     ans = new BatchNormComponent();
   } else if (component_type == "TimeHeightConvolutionComponent") {
     ans = new TimeHeightConvolutionComponent();
+  } else if (component_type == "RestrictedAttentionComponent") {
+    ans = new RestrictedAttentionComponent();
   } else if (component_type == "SumBlockComponent") {
     ans = new SumBlockComponent();
   }
diff --git a/src/nnet3/nnet-test-utils.cc b/src/nnet3/nnet-test-utils.cc
index a138fcacceb..47a040a1789 100644
--- a/src/nnet3/nnet-test-utils.cc
+++ b/src/nnet3/nnet-test-utils.cc
@@ -1076,6 +1076,63 @@ void GenerateConfigSequenceCnnNew(
 }
 
 
+
+void GenerateConfigSequenceRestrictedAttention(
+    const NnetGenerationOptions &opts,
+    std::vector<std::string> *configs) {
+  std::ostringstream ss;
+
+
+  int32 input_dim = RandInt(100, 150),
+      num_heads = RandInt(1, 2),
+      key_dim = RandInt(20, 40),
+      value_dim = RandInt(20, 40),
+      time_stride = RandInt(1, 3),
+      num_left_inputs = RandInt(1, 4),
+      num_right_inputs = RandInt(0, 2),
+      num_left_inputs_required = RandInt(0, num_left_inputs),
+      num_right_inputs_required = RandInt(0, num_right_inputs);
+  bool output_context = (RandInt(0, 1) == 0);
+  int32 context_dim = (num_left_inputs + 1 + num_right_inputs),
+      query_dim = key_dim + context_dim;
+  int32 attention_input_dim = num_heads * (key_dim + value_dim + query_dim);
+
+  std::string cur_layer_descriptor = "input";
+
+  { // input layer.
+    ss << "input-node name=input dim=" << input_dim
+       << std::endl;
+  }
+
+  { // affine component
+    ss << "component name=affine type=NaturalGradientAffineComponent input-dim="
+       << input_dim << " output-dim=" << attention_input_dim << std::endl;
+    ss << "component-node name=affine component=affine input=input"
+       << std::endl;
+  }
+
+  { // attention component
+    ss << "component-node name=attention component=attention input=affine"
+       << std::endl;
+    ss << "component name=attention type=RestrictedAttentionComponent"
+       << " num-heads=" << num_heads << " key-dim=" << key_dim
+       << " value-dim=" << value_dim << " time-stride=" << time_stride
+       << " num-left-inputs=" << num_left_inputs << " num-right-inputs="
+       << num_right_inputs << " num-left-inputs-required="
+       << num_left_inputs_required << " num-right-inputs-required="
+       << num_right_inputs_required
+       << " output-context=" << (output_context ? "true" : "false")
+       << (RandInt(0, 1) == 0 ? " key-scale=1.0" : "")
+       << std::endl;
+  }
+
+  { // output
+    ss << "output-node name=output input=attention" << std::endl;
+  }
+  configs->push_back(ss.str());
+}
+
+
 // generates a config sequence involving DistributeComponent.
 void GenerateConfigSequenceDistribute(
     const NnetGenerationOptions &opts,
@@ -1212,11 +1269,16 @@ void GenerateConfigSequence(
       // We're allocating more case statements to the most recently
       // added type of model, to give more thorough testing where
       // it's needed most.
-    case 12: case 13: case 14:
+    case 12:
       if (!opts.allow_nonlinearity || !opts.allow_context)
         goto start;
       GenerateConfigSequenceCnnNew(opts, configs);
       break;
+    case 13: case 14:
+      if (!opts.allow_nonlinearity || !opts.allow_context)
+        goto start;
+      GenerateConfigSequenceRestrictedAttention(opts, configs);
+      break;
     default:
       KALDI_ERR << "Error generating config sequence.";
   }