From 09b367057998afc8c95391a698700bb076b03472 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Tue, 16 Jul 2019 17:35:20 +0200 Subject: [PATCH] updates --- train.py | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/train.py b/train.py index 68e0c3ca..2c4fbe84 100644 --- a/train.py +++ b/train.py @@ -167,12 +167,11 @@ def train(cfg, maps = np.zeros(nc) # mAP per class results = (0, 0, 0, 0, 0) # P, R, mAP, F1, test_loss n_burnin = min(round(nb / 5 + 1), 1000) # burn-in batches - t, t0 = time.time(), time.time() torch.cuda.empty_cache() for epoch in range(start_epoch, epochs): model.train() - print(('\n%8s%12s' + '%10s' * 7) % - ('Epoch', 'Batch', 'GIoU/xy', 'wh', 'obj', 'cls', 'total', 'targets', 'img_size')) + print(('\n%8s' + '%10s' * 8) % + ('Epoch', 'GIoU/xy', 'wh', 'obj', 'cls', 'total', 'targets', 'img_size', 'gpu_mem')) # Update scheduler scheduler.step() @@ -236,10 +235,8 @@ def train(cfg, # Print batch results mloss = (mloss * i + loss_items) / (i + 1) # update mean losses - # s = ('%8s%12s' + '%10.3g' * 7) % ('%g/%g' % (epoch, epochs - 1), '%g/%g' % (i, nb - 1), *mloss, len(targets), time.time() - t) - s = ('%8s%12s' + '%10.3g' * 7) % ( - '%g/%g' % (epoch, epochs - 1), '%g/%g' % (i, nb - 1), *mloss, len(targets), img_size) - t = time.time() + mem = torch.cuda.memory_cached() if torch.cuda.is_available() else 0 + s = ('%8s' + '%10.3g' * 8) % ('%g/%g' % (epoch, epochs - 1), *mloss, len(targets), img_size, mem) pbar.set_description(s) # print(s) # Report time