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_base_ = [
'../_base_/datasets/semantickitti.py', '../_base_/models/cylinder3d.py',
'../_base_/default_runtime.py'
]
# optimizer
lr = 0.001
optim_wrapper = dict(
type='OptimWrapper',
optimizer=dict(type='AdamW', lr=lr, weight_decay=0.01))
train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=36, 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=1000),
dict(
type='MultiStepLR',
begin=0,
end=36,
by_epoch=True,
milestones=[30],
gamma=0.1)
]
train_dataloader = dict(batch_size=4, )
# Default setting for scaling LR automatically
# - `enable` means enable scaling LR automatically
# or not by default.
# - `base_batch_size` = (8 GPUs) x (4 samples per GPU).
# auto_scale_lr = dict(enable=False, base_batch_size=32)
default_hooks = dict(checkpoint=dict(type='CheckpointHook', interval=5))
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