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# Note: This schedule config serves as a base config for other schedules. | |
# Users would have to at least fill in "max_epochs" and "val_interval" | |
# in order to use this config in their experiments. | |
# optimizer | |
optim_wrapper = dict(type='OptimWrapper', optimizer=dict(type='Adam', lr=3e-4)) | |
train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=None, val_interval=1) | |
val_cfg = dict(type='ValLoop') | |
test_cfg = dict(type='TestLoop') | |
# learning policy | |
param_scheduler = [ | |
dict(type='ConstantLR', factor=1.0), | |
] | |