Remove stupid datatypes. Begin code cleanup

git-svn-id: svn://mattst88.com/svn/cleanbench/trunk@5 0d43b9a7-5ab2-4d7b-af9d-f64450cef757

1 files changed, 8 insertions, 8 deletions

diff --git a/neural.c b/neural.c
index 0a1bced..04d49fe 100644
--- a/neural.c
+++ b/neural.c
@@ -50,7 +50,7 @@ void DoNNET(void)
 {
 NNetStruct *locnnetstruct;      /* Local ptr to global data */
 char *errorcontext;
-ulong accumtime;
+unsigned long accumtime;
 double iterations;
 
 /*
@@ -72,7 +72,7 @@ errorcontext="CPU:NNET";
 **  the initial neural net state.
 */
 /* randnum(3L); */
-randnum((int32)3);
+randnum((int32_t)3);
 
 /*
 ** Read in the input and output patterns.  We'll do this
@@ -97,7 +97,7 @@ if(locnnetstruct->adjust==0)
 	  locnnetstruct->loops<MAXNNETLOOPS;
 	  locnnetstruct->loops++)
 	  {     /*randnum(3L); */
-		randnum((int32)3);
+		randnum((int32_t)3);
 		if(DoNNetIteration(locnnetstruct->loops)
 			>global_min_ticks) break;
 	  }
@@ -111,7 +111,7 @@ iterations=(double)0.0;
 
 do {
 	/* randnum(3L); */    /* Gotta do this for Neural Net */
-	randnum((int32)3);    /* Gotta do this for Neural Net */
+	randnum((int32_t)3);    /* Gotta do this for Neural Net */
 	accumtime+=DoNNetIteration(locnnetstruct->loops);
 	iterations+=(double)locnnetstruct->loops;
 } while(TicksToSecs(accumtime)<locnnetstruct->request_secs);
@@ -135,9 +135,9 @@ return;
 ** Do a single iteration of the neural net benchmark.
 ** By iteration, we mean a "learning" pass.
 */
-static ulong DoNNetIteration(ulong nloops)
+static unsigned long DoNNetIteration(unsigned long nloops)
 {
-ulong elapsed;          /* Elapsed time */
+unsigned long elapsed;          /* Elapsed time */
 int patt;
 
 /*
@@ -602,7 +602,7 @@ for (neurode = 0; neurode<MID_SIZE; neurode++)
 	for(i=0; i<IN_SIZE; i++)
 	{
 	        /* value=(double)abs_randwc(100000L); */
-		value=(double)abs_randwc((int32)100000);
+		value=(double)abs_randwc((int32_t)100000);
 		value=value/(double)100000.0 - (double) 0.5;
 		mid_wts[neurode][i] = value/2;
 	}
@@ -612,7 +612,7 @@ for (neurode=0; neurode<OUT_SIZE; neurode++)
 	for(i=0; i<MID_SIZE; i++)
 	{
 	        /* value=(double)abs_randwc(100000L); */
-		value=(double)abs_randwc((int32)100000);
+		value=(double)abs_randwc((int32_t)100000);
 		value=value/(double)10000.0 - (double) 0.5;
 		out_wts[neurode][i] = value/2;
 	}