Fixing GCC 4.4 -std=gnu++0x compilation issues

src/nnet2bin/nnet-shuffle-egs.cc

@@ -32,13 +32,13 @@ int main(int argc, char *argv[]) {
 
     const char *usage =
         "Copy examples (typically single frames) for neural network training,\n"
-        "from the input to output, but randomly shuffle the order.  This program will keep\n"
+        "from the input to output, but randomly shuffle the order. This program will keep\n"
         "all of the examples in memory at once, so don't give it too many.\n"
         "\n"
         "Usage:  nnet-shuffle-egs [options] <egs-rspecifier> <egs-wspecifier>\n"
         "\n"
         "nnet-shuffle-egs --srand=1 ark:train.egs ark:shuffled.egs\n";
-    
+
     int32 srand_seed = 0;
     int32 buffer_size = 0;
     ParseOptions po(usage);
@@ -46,11 +46,11 @@ int main(int argc, char *argv[]) {
     po.Register("buffer-size", &buffer_size, "If >0, size of a buffer we use "
                 "to do limited-memory partial randomization.  Otherwise, do "
                 "full randomization.");
-    
+
     po.Read(argc, argv);
 
     srand(srand_seed);
-    
+
     if (po.NumArgs() != 2) {
       po.PrintUsage();
       exit(1);
@@ -64,22 +64,23 @@ int main(int argc, char *argv[]) {
     std::vector<std::pair<std::string, NnetExample*> > egs;
     SequentialNnetExampleReader example_reader(examples_rspecifier);
     NnetExampleWriter example_writer(examples_wspecifier);
-    if (buffer_size == 0) { // Do full randomization
+    if (buffer_size == 0) {  // Do full randomization
       // Putting in an extra level of indirection here to avoid excessive
       // computation and memory demands when we have to resize the vector.
-    
+
       for (; !example_reader.Done(); example_reader.Next())
-        egs.push_back(std::make_pair(example_reader.Key(), 
+        egs.push_back(std::make_pair(example_reader.Key(),
                                     new NnetExample(example_reader.Value())));
-      
+
       std::random_shuffle(egs.begin(), egs.end());
     } else {
       KALDI_ASSERT(buffer_size > 0);
-      egs.resize(buffer_size, std::pair<std::string, NnetExample*>("", NULL));
+      egs.resize(buffer_size, 
+          std::pair<std::string, NnetExample*>("", static_cast<NnetExample *>(NULL)));
       for (; !example_reader.Done(); example_reader.Next()) {
         int32 index = RandInt(0, buffer_size - 1);
         if (egs[index].second == NULL) {
-          egs[index] = std::make_pair(example_reader.Key(), 
+          egs[index] = std::make_pair(example_reader.Key(),
                                     new NnetExample(example_reader.Value()));
         } else {
           example_writer.Write(egs[index].first, *(egs[index].second));
@@ -87,7 +88,7 @@ int main(int argc, char *argv[]) {
           *(egs[index].second) = example_reader.Value();
           num_done++;
         }
-      }      
+      }
     }
     for (size_t i = 0; i < egs.size(); i++) {
       if (egs[i].second != NULL) {
@@ -100,7 +101,7 @@ int main(int argc, char *argv[]) {
     KALDI_LOG << "Shuffled order of " << num_done
               << " neural-network training examples "
               << (buffer_size ? "using a buffer (partial randomization)" : "");
-                  
+
     return (num_done == 0 ? 1 : 0);
   } catch(const std::exception &e) {
     std::cerr << e.what() << '\n';