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# training schedule for 2x | |
train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=24, val_interval=1) | |
val_cfg = dict(type='ValLoop') | |
test_cfg = dict(type='TestLoop') | |
# learning rate | |
param_scheduler = [ | |
dict( | |
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500), | |
dict( | |
type='MultiStepLR', | |
begin=0, | |
end=24, | |
by_epoch=True, | |
milestones=[16, 22], | |
gamma=0.1) | |
] | |
# optimizer | |
optim_wrapper = dict( | |
type='OptimWrapper', | |
optimizer=dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001)) | |
# Default setting for scaling LR automatically | |
# - `enable` means enable scaling LR automatically | |
# or not by default. | |
# - `base_batch_size` = (8 GPUs) x (2 samples per GPU). | |
auto_scale_lr = dict(enable=False, base_batch_size=16) | |