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car-detection-bayes
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multi_gpu multi_scale

This commit is contained in:
Glenn Jocher 2019-03-19 12:34:12 +02:00
parent feb5fcb16f
commit 76f555c108
1 changed files with 5 additions and 1 deletions
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6
train.py
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@ -25,6 +25,8 @@ def train(
if multi_scale: # pass maximum multi_scale size if multi_scale: # pass maximum multi_scale size
img_size = 608 img_size = 608
ms_index = -1
ms_sizes = [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
else: else:
torch.backends.cudnn.benchmark = True # unsuitable for multiscale torch.backends.cudnn.benchmark = True # unsuitable for multiscale
@ -153,7 +155,9 @@ def train(
# Multi-Scale training (320 - 608 pixels) every 10 batches # Multi-Scale training (320 - 608 pixels) every 10 batches
if multi_scale and (i + 1) % 10 == 0: if multi_scale and (i + 1) % 10 == 0:
dataloader.img_size = random.choice(range(10, 20)) * 32 ms_index += 1
dataloader.img_size = ms_sizes[ms_index]
# dataloader.img_size = random.choice(range(10, 20)) * 32
print('multi_scale img_size = %g' % dataloader.img_size) print('multi_scale img_size = %g' % dataloader.img_size)
# Update best loss # Update best loss