diff --git a/src/nnet2f32.c b/src/nnet2f32.c
index 2a9a288..ac57085 100644
--- a/src/nnet2f32.c
+++ b/src/nnet2f32.c
@@ -1,7 +1,7 @@
 /*
   nnet2f32.c
 
-  Writes current compiled-in model to a binary file of floats.
+  Writes current compiled-in model to a binary file of floats, and runs a few tests.
 */
 
 #include <assert.h>
diff --git a/src/nnet_rw.c b/src/nnet_rw.c
index f2c56eb..5cdf598 100644
--- a/src/nnet_rw.c
+++ b/src/nnet_rw.c
@@ -9,6 +9,7 @@
 #include <stdio.h>
 #include <stdlib.h>
 #include <string.h>
+#include <stdint.h>
 #include "nnet_data.h"
 #include "nnet_rw.h"
 
@@ -177,25 +178,11 @@ void read_gru_weights(char *name, const GRULayer *l, FILE *f32) {
     ret = fread(l->recurrent_weights, sizeof(float), nrecurrent, f32); assert(ret == nrecurrent);
 }
 
-int sparse_sgemv_count_idx(int rows, const int *idx)
-{
-   int i, j;
-   int count = 0;
-   for (i=0;i<rows;i+=16) {
-      int cols;
-      cols = *idx++; count++;
-      for (j=0;j<cols;j++) {
-	  idx++; count++;
-      }
-   }
-   return count; 
-}
-
 void write_sparse_gru_weights(char *name, const SparseGRULayer *l, FILE *f32) {
     int nbias = l->nb_neurons*6;
     int ndiag = l->nb_neurons*3;
     int nrecurrent = l->nb_neurons*l->nb_neurons*3;
-    int nidx = sparse_sgemv_count_idx(ndiag, l->idx);
+    int nidx = 32767;
     printf("%s: %d %d %d %d\n", name, nbias, ndiag, nrecurrent, nidx);
     fwrite(l->bias, sizeof(float), nbias, f32);
     fwrite(l->diag_weights, sizeof(float), ndiag, f32);
@@ -207,7 +194,7 @@ void check_sparse_gru_weights(char *name, const SparseGRULayer *l, FILE *f32) {
     int nbias = l->nb_neurons*6;
     int ndiag = l->nb_neurons*3;
     int nrecurrent = l->nb_neurons*l->nb_neurons*3;
-    int nidx = sparse_sgemv_count_idx(ndiag, l->idx);
+    int nidx = 32767;
     printf("%s: %d %d %d %d", name, nbias, ndiag, nrecurrent, nidx);
     check(l->bias, nbias, f32);
     check(l->diag_weights, ndiag, f32);
@@ -220,9 +207,9 @@ void read_sparse_gru_weights(char *name, const SparseGRULayer *l, FILE *f32) {
     int nbias = l->nb_neurons*6;
     int ndiag = l->nb_neurons*3;
     int nrecurrent = l->nb_neurons*l->nb_neurons*3;
-    int nidx = sparse_sgemv_count_idx(ndiag, l->idx);
-    printf("%s: %d %d %d %d\n", name, nbias, ndiag, nrecurrent, nidx);
     int ret;
+    int nidx = 32767;
+    printf("%s: %d %d %d %d\n", name, nbias, ndiag, nrecurrent, nidx);
     ret = fread(l->bias, sizeof(float), nbias, f32); assert(ret == nbias);
     ret = fread(l->diag_weights, sizeof(float), ndiag, f32); assert(ret == ndiag);
     ret = fread(l->recurrent_weights, sizeof(float), nrecurrent, f32); assert(ret == nrecurrent);