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car-detection-bayes
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burnin lr ramp 300 iterations

This commit is contained in:
Glenn Jocher 2020-03-30 19:27:42 -07:00
parent ac2aa56e0a
commit b2d9f1898f
1 changed files with 14 additions and 13 deletions
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27
train.py
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@ -241,23 +241,16 @@ def train():
targets = targets.to(device)
# Hyperparameter Burn-in
n_burn = 200 # number of burn-in batches
n_burn = 300 # number of burn-in batches
if ni <= n_burn:
# g = (ni / n_burn) ** 2 # gain
g = (ni / n_burn) ** 2 # gain
for x in model.named_modules(): # initial stats may be poor, wait to track
if x[0].endswith('BatchNorm2d'):
x[1].track_running_stats = ni == n_burn
# for x in optimizer.param_groups:
# x['lr'] = x['initial_lr'] * lf(epoch) * g # gain rises from 0 - 1
# if 'momentum' in x:
# x['momentum'] = hyp['momentum'] * g
# Plot images with bounding boxes
if ni < 1:
f = 'train_batch%g.png' % i # filename
plot_images(imgs=imgs, targets=targets, paths=paths, fname=f)
if tb_writer:
tb_writer.add_image(f, cv2.imread(f)[:, :, ::-1], dataformats='HWC')
for x in optimizer.param_groups:
x['lr'] = x['initial_lr'] * lf(epoch) * g # gain rises from 0 - 1
if 'momentum' in x:
x['momentum'] = hyp['momentum'] * g
# Multi-Scale training
if opt.multi_scale:
@ -299,6 +292,14 @@ def train():
s = ('%10s' * 2 + '%10.3g' * 6) % ('%g/%g' % (epoch, epochs - 1), mem, *mloss, len(targets), img_size)
pbar.set_description(s)
# Plot images with bounding boxes
if ni < 1:
f = 'train_batch%g.png' % i # filename
plot_images(imgs=imgs, targets=targets, paths=paths, fname=f)
if tb_writer:
tb_writer.add_image(f, cv2.imread(f)[:, :, ::-1], dataformats='HWC')
# tb_writer.add_graph(model, imgs)
# end batch ------------------------------------------------------------------------------------------------
# Update scheduler