Fix format string conversion specifiers (#6192)

Signed-off-by: Juuso Alasuutari <[email protected]>
Co-authored-by: Stefano Sinigardi <[email protected]>

src/blas.c

@@ -594,7 +594,7 @@ float find_sim(size_t i, size_t j, contrastive_params *contrast_p, int contrast_
         if (contrast_p[z].i == i && contrast_p[z].j == j) break;
     }
     if (z == contrast_p_size) {
-        printf(" Error: find_sim(): sim isn't found: i = %d, j = %d, z = %d \n", i, j, z);
+        printf(" Error: find_sim(): sim isn't found: i = %zu, j = %zu, z = %zu \n", i, j, z);
         getchar();
     }
 
@@ -608,7 +608,7 @@ float find_P_constrastive(size_t i, size_t j, contrastive_params *contrast_p, in
         if (contrast_p[z].i == i && contrast_p[z].j == j) break;
     }
     if (z == contrast_p_size) {
-        printf(" Error: find_P_constrastive(): P isn't found: i = %d, j = %d, z = %d \n", i, j, z);
+        printf(" Error: find_P_constrastive(): P isn't found: i = %zu, j = %zu, z = %zu \n", i, j, z);
         getchar();
     }
 
@@ -648,7 +648,7 @@ float P_constrastive_f_det(size_t il, int *labels, float **z, unsigned int featu
 float P_constrastive_f(size_t i, size_t l, int *labels, float **z, unsigned int feature_size, float temperature, contrastive_params *contrast_p, int contrast_p_size)
 {
     if (i == l) {
-        fprintf(stderr, " Error: in P_constrastive must be i != l, while i = %d, l = %d \n", i, l);
+        fprintf(stderr, " Error: in P_constrastive must be i != l, while i = %zu, l = %zu \n", i, l);
         getchar();
     }
 
@@ -782,7 +782,7 @@ void grad_contrastive_loss_negative_f(size_t i, int *class_ids, int *labels, siz
 float P_constrastive(size_t i, size_t l, int *labels, size_t num_of_samples, float **z, unsigned int feature_size, float temperature, float *cos_sim, float *exp_cos_sim)
 {
     if (i == l) {
-        fprintf(stderr, " Error: in P_constrastive must be i != l, while i = %d, l = %d \n", i, l);
+        fprintf(stderr, " Error: in P_constrastive must be i != l, while i = %zu, l = %zu \n", i, l);
         getchar();
     }
 

src/captcha.c

@@ -85,7 +85,7 @@ void train_captcha(char *cfgfile, char *weightfile)
         float loss = train_network(net, train);
         if(avg_loss == -1) avg_loss = loss;
         avg_loss = avg_loss*.9 + loss*.1;
-        printf("%d: %f, %f avg, %lf seconds, %ld images\n", i, loss, avg_loss, sec(clock()-time), *net.seen);
+        printf("%d: %f, %f avg, %lf seconds, %" PRIu64 " images\n", i, loss, avg_loss, sec(clock()-time), *net.seen);
         free_data(train);
         if(i%100==0){
             char buff[256];

src/cifar.c

@@ -29,7 +29,7 @@ void train_cifar(char *cfgfile, char *weightfile)
         float loss = train_network_sgd(net, train, 1);
         if(avg_loss == -1) avg_loss = loss;
         avg_loss = avg_loss*.95 + loss*.05;
-        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %ld images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
+        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %" PRIu64 " images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
         if(*net.seen/N > epoch){
             epoch = *net.seen/N;
             char buff[256];
@@ -85,7 +85,7 @@ void train_cifar_distill(char *cfgfile, char *weightfile)
         float loss = train_network_sgd(net, train, 1);
         if(avg_loss == -1) avg_loss = loss;
         avg_loss = avg_loss*.95 + loss*.05;
-        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %ld images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
+        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %" PRIu64 " images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
         if(*net.seen/N > epoch){
             epoch = *net.seen/N;
             char buff[256];

src/classifier.c

@@ -208,7 +208,7 @@ void train_classifier(char *datacfg, char *cfgfile, char *weightfile, int *gpus,
         if (avg_time < 0) avg_time = time_remaining;
         else avg_time = alpha_time * time_remaining + (1 -  alpha_time) * avg_time;
         start = what_time_is_it_now();
-        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %ld images, %f hours left\n", get_current_batch(net), (float)(*net.seen)/ train_images_num, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen, avg_time);
+        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %" PRIu64 " images, %f hours left\n", get_current_batch(net), (float)(*net.seen)/ train_images_num, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen, avg_time);
 #ifdef OPENCV
         if (net.contrastive) {
             float cur_con_acc = -1;

src/compare.c

@@ -1,12 +1,12 @@
-#include <stdio.h>
-
 #include "network.h"
 #include "detection_layer.h"
 #include "cost_layer.h"
 #include "utils.h"
 #include "parser.h"
 #include "box.h"
 
+#include <stdio.h>
+
 void train_compare(char *cfgfile, char *weightfile)
 {
     srand(time(0));
@@ -54,7 +54,7 @@ void train_compare(char *cfgfile, char *weightfile)
         float loss = train_network(net, train);
         if(avg_loss == -1) avg_loss = loss;
         avg_loss = avg_loss*.9 + loss*.1;
-        printf("%.3f: %f, %f avg, %lf seconds, %ld images\n", (float)*net.seen/N, loss, avg_loss, sec(clock()-time), *net.seen);
+        printf("%.3f: %f, %f avg, %lf seconds, %" PRIu64 " images\n", (float)*net.seen/N, loss, avg_loss, sec(clock()-time), *net.seen);
         free_data(train);
         if(i%100 == 0){
             char buff[256];

src/dark_cuda.c

@@ -385,14 +385,14 @@ void free_pinned_memory()
 void pre_allocate_pinned_memory(const size_t size)
 {
     const size_t num_of_blocks = size / pinned_block_size + ((size % pinned_block_size) ? 1 : 0);
-    printf("pre_allocate... pinned_ptr = %p \n", pinned_ptr);
+    printf("pre_allocate... pinned_ptr = %p \n", (void *)pinned_ptr);
 
     pthread_mutex_lock(&mutex_pinned);
     if (!pinned_ptr) {
         pinned_ptr = (float **)calloc(num_of_blocks, sizeof(float *));
         if(!pinned_ptr) error("calloc failed in pre_allocate()", DARKNET_LOC);
 
-        printf("pre_allocate: size = %Iu MB, num_of_blocks = %Iu, block_size = %Iu MB \n",
+        printf("pre_allocate: size = %zu MB, num_of_blocks = %zu, block_size = %zu MB \n",
             size / (1024*1024), num_of_blocks, pinned_block_size / (1024 * 1024));
 
         int k;
@@ -402,7 +402,7 @@ void pre_allocate_pinned_memory(const size_t size)
             CHECK_CUDA(status);
             if (!pinned_ptr[k]) error("cudaHostAlloc failed", DARKNET_LOC);
             else {
-                printf(" Allocated %d pinned block \n", pinned_block_size);
+                printf(" Allocated %zu pinned block \n", pinned_block_size);
             }
         }
         pinned_num_of_blocks = num_of_blocks;
@@ -423,7 +423,7 @@ float *cuda_make_array_pinned_preallocated(float *x, size_t n)
     {
         if ((allocation_size + pinned_index) > pinned_block_size) {
             const float filled = (float)100 * pinned_index / pinned_block_size;
-            printf("\n Pinned block_id = %d, filled = %f %% \n", pinned_block_id, filled);
+            printf("\n Pinned block_id = %zu, filled = %f %% \n", pinned_block_id, filled);
             pinned_block_id++;
             pinned_index = 0;
         }
@@ -438,13 +438,13 @@ float *cuda_make_array_pinned_preallocated(float *x, size_t n)
 
     if(!x_cpu) {
         if (allocation_size > pinned_block_size / 2) {
-            printf("Try to allocate new pinned memory, size = %d MB \n", size / (1024 * 1024));
+            printf("Try to allocate new pinned memory, size = %zu MB \n", size / (1024 * 1024));
             cudaError_t status = cudaHostAlloc((void **)&x_cpu, size, cudaHostRegisterMapped);
             if (status != cudaSuccess) fprintf(stderr, " Can't allocate CUDA-pinned memory on CPU-RAM (pre-allocated memory is over too) \n");
             CHECK_CUDA(status);
         }
         else {
-            printf("Try to allocate new pinned BLOCK, size = %d MB \n", size / (1024 * 1024));
+            printf("Try to allocate new pinned BLOCK, size = %zu MB \n", size / (1024 * 1024));
             pinned_num_of_blocks++;
             pinned_block_id = pinned_num_of_blocks - 1;
             pinned_index = 0;

src/dice.c

@@ -33,7 +33,7 @@ void train_dice(char *cfgfile, char *weightfile)
         float loss = train_network(net, train);
         if(avg_loss == -1) avg_loss = loss;
         avg_loss = avg_loss*.9 + loss*.1;
-        printf("%d: %f, %f avg, %lf seconds, %ld images\n", i, loss, avg_loss, sec(clock()-time), *net.seen);
+        printf("%d: %f, %f avg, %lf seconds, %" PRIu64 " images\n", i, loss, avg_loss, sec(clock()-time), *net.seen);
         free_data(train);
         if((i % 100) == 0) net.learning_rate *= .1;
         if(i%100==0){

src/go.c

@@ -142,7 +142,7 @@ void train_go(char *cfgfile, char *weightfile)
         float loss = train_network_datum(net, board, move) / net.batch;
         if(avg_loss == -1) avg_loss = loss;
         avg_loss = avg_loss*.95 + loss*.05;
-        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %ld images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
+        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %" PRIu64 " images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
         if(*net.seen/N > epoch){
             epoch = *net.seen/N;
             char buff[256];

src/http_stream.cpp

@@ -508,7 +508,7 @@ class MJPG_sender
                 }
 
                 char head[400];
-                sprintf(head, "--mjpegstream\r\nContent-Type: image/jpeg\r\nContent-Length: %zu\r\n\r\n", outlen);
+                sprintf(head, "--mjpegstream\r\nContent-Type: image/jpeg\r\nContent-Length: %d\r\n\r\n", outlen);
                 _write(s, head, 0);
                 int n = _write(s, (char*)(&outbuf[0]), outlen);
                 cerr << "known client: " << s << ", sent = " << n << ", must be sent outlen = " << outlen << endl;

src/network.h

@@ -1,6 +1,17 @@
 // Oh boy, why am I about to do this....
 #ifndef NETWORK_H
 #define NETWORK_H
+
+/*
+ * Necessary in C++ to get format macros out of inttypes.h
+ */
+#ifdef __cplusplus
+#ifndef __STDC_FORMAT_MACROS
+#define __STDC_FORMAT_MACROS 1
+#endif
+#endif
+#include <inttypes.h>
+
 #include "darknet.h"
 
 #include <stdint.h>

src/softmax_layer.c

@@ -200,7 +200,7 @@ contrastive_layer make_contrastive_layer(int batch, int w, int h, int c, int cla
     printf(" max_contr_size = %d MB \n", max_contr_size / (1024*1024));
     l.contrast_p_gpu = (contrastive_params *)cuda_make_array(NULL, max_contr_size);
 #endif
-    fprintf(stderr, "contrastive %4d x%4d x%4d x emb_size %4d x batch: %4d  classes = %4d, step = %4d \n", w, h, l.n, l.embedding_size, batch, l.classes, step);
+    fprintf(stderr, "contrastive %4d x%4d x%4d x emb_size %4d x batch: %4d  classes = %4d, step = %4zu \n", w, h, l.n, l.embedding_size, batch, l.classes, step);
     if(l.detection) fprintf(stderr, "detection \n");
     return l;
 }

src/tag.c

@@ -63,7 +63,7 @@ void train_tag(char *cfgfile, char *weightfile, int clear)
         float loss = train_network(net, train);
         if(avg_loss == -1) avg_loss = loss;
         avg_loss = avg_loss*.9 + loss*.1;
-        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %ld images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
+        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %" PRIu64 " images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
         free_data(train);
         if(*net.seen/N > epoch){
             epoch = *net.seen/N;

src/writing.c

@@ -65,7 +65,7 @@ void train_writing(char *cfgfile, char *weightfile)
 
         if(avg_loss == -1) avg_loss = loss;
         avg_loss = avg_loss*.9 + loss*.1;
-        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %ld images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
+        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %" PRIu64 " images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
         free_data(train);
         if(get_current_batch(net)%100 == 0){
             char buff[256];