refine

tools/infer/predict.py

@@ -145,10 +145,6 @@ def main():
             output = output.flatten()
             if i >= 10:
                 test_time += time.time() - start_time
-            cls = np.argmax(output)
-            score = output[cls]
-            logger.info("class: {0}".format(cls))
-            logger.info("score: {0}".format(score))
 
         fp_message = "FP16" if args.use_fp16 else "FP32"
         logger.info("{0}\t{1}\tbatch size: {2}\ttime(ms): {3}".format(

tools/program.py

@@ -385,7 +385,7 @@ def run(dataloader, exe, program, fetchs, epoch=0, mode='train'):
             metric_list[i].update(m[0], len(batch[0]))
         fetchs_str = ''.join([str(m.value)+' '
                               for m in metric_list]+ [batch_time.value])
-        logger.info("epoch:{:<3d} {:s} step:{:<4d} {:s}".format(
+        logger.info("epoch:{:<3d} {:s} step:{:<4d} {:s}s".format(
             epoch, mode, idx, fetchs_str))
     end_str = ''.join([str(m.mean)+' ' for m in metric_list] + [batch_time.total])
-    logger.info("END epoch:{:<3d} {:s} {:s}".format(epoch, mode, end_str))
+    logger.info("END epoch:{:<3d} {:s} {:s}s".format(epoch, mode, end_str))