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car-detection-bayes
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This commit is contained in:
Glenn Jocher 2020-02-27 13:40:14 -08:00
parent 0fb4a46ace
commit d5815ebfd2
1 changed files with 4 additions and 4 deletions
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train.py
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@ -132,6 +132,10 @@ def train():
# possible weights are '*.weights', 'yolov3-tiny.conv.15', 'darknet53.conv.74' etc. # possible weights are '*.weights', 'yolov3-tiny.conv.15', 'darknet53.conv.74' etc.
load_darknet_weights(model, weights) load_darknet_weights(model, weights)
# Mixed precision training https://github.com/NVIDIA/apex
if mixed_precision:
model, optimizer = amp.initialize(model, optimizer, opt_level='O1', verbosity=0)
# Scheduler https://github.com/ultralytics/yolov3/issues/238 # Scheduler https://github.com/ultralytics/yolov3/issues/238
# lf = lambda x: 1 - x / epochs # linear ramp to zero # lf = lambda x: 1 - x / epochs # linear ramp to zero
# lf = lambda x: 10 ** (hyp['lrf'] * x / epochs) # exp ramp # lf = lambda x: 10 ** (hyp['lrf'] * x / epochs) # exp ramp
@ -153,10 +157,6 @@ def train():
# plt.tight_layout() # plt.tight_layout()
# plt.savefig('LR.png', dpi=300) # plt.savefig('LR.png', dpi=300)
# Mixed precision training https://github.com/NVIDIA/apex
if mixed_precision:
model, optimizer = amp.initialize(model, optimizer, opt_level='O1', verbosity=0)
# Initialize distributed training # Initialize distributed training
if device.type != 'cpu' and torch.cuda.device_count() > 1: if device.type != 'cpu' and torch.cuda.device_count() > 1:
dist.init_process_group(backend='nccl', # 'distributed backend' dist.init_process_group(backend='nccl', # 'distributed backend'