* New flag 'stop_training' in util.callbacks.Callbacks class to prematurely stop training from callback handler * Removed most of the new checks, leaving only the one after calling 'on_train_batch_end' * Cleanup Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>modifyDataloader
@@ -352,6 +352,8 @@ def train(hyp, # path/to/hyp.yaml or hyp dictionary | |||
pbar.set_description(('%10s' * 2 + '%10.4g' * 5) % ( | |||
f'{epoch}/{epochs - 1}', mem, *mloss, targets.shape[0], imgs.shape[-1])) | |||
callbacks.run('on_train_batch_end', ni, model, imgs, targets, paths, plots, opt.sync_bn) | |||
if callbacks.stop_training: | |||
return | |||
# end batch ------------------------------------------------------------------------------------------------ | |||
# Scheduler |
@@ -35,6 +35,7 @@ class Callbacks: | |||
'on_params_update': [], | |||
'teardown': [], | |||
} | |||
self.stop_training = False # set True to interrupt training | |||
def register_action(self, hook, name='', callback=None): | |||
""" |