mmselfsup/configs/selfsup/simclr/simclr_resnet50_8xb32-coslr...

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Python

_base_ = [
'../_base_/models/simclr.py',
'../_base_/datasets/imagenet_simclr.py',
'../_base_/schedules/lars_coslr-200e_in1k.py',
'../_base_/default_runtime.py',
]
# optimizer
optimizer = dict(
type='LARS',
lr=0.3,
momentum=0.9,
weight_decay=1e-6,
paramwise_options={
'(bn|gn)(\\d+)?.(weight|bias)':
dict(weight_decay=0., lars_exclude=True),
'bias': dict(weight_decay=0., lars_exclude=True)
})
# learning policy
lr_config = dict(
policy='CosineAnnealing',
min_lr=0.,
warmup='linear',
warmup_iters=10,
warmup_ratio=1e-4,
warmup_by_epoch=True)
# runtime settings
# the max_keep_ckpts controls the max number of ckpt file in your work_dirs
# if it is 3, when CheckpointHook (in mmcv) saves the 4th ckpt
# it will remove the oldest one to keep the number of total ckpts as 3
checkpoint_config = dict(interval=10, max_keep_ckpts=3)