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Running
on
A10G
Running
on
A10G
_base_ = [ | |
'../../configs/_base_/models/upernet_uniformer.py', | |
'../../configs/_base_/datasets/ade20k.py', | |
'../../configs/_base_/default_runtime.py', | |
'../../configs/_base_/schedules/schedule_160k.py' | |
] | |
model = dict( | |
backbone=dict( | |
type='UniFormer', | |
embed_dim=[64, 128, 320, 512], | |
layers=[3, 4, 8, 3], | |
head_dim=64, | |
drop_path_rate=0.25, | |
windows=True, | |
hybrid=False, | |
window_size=32 | |
), | |
decode_head=dict( | |
in_channels=[64, 128, 320, 512], | |
num_classes=150 | |
), | |
auxiliary_head=dict( | |
in_channels=320, | |
num_classes=150 | |
)) | |
# AdamW optimizer, no weight decay for position embedding & layer norm in backbone | |
optimizer = dict(_delete_=True, type='AdamW', lr=0.00006, betas=(0.9, 0.999), weight_decay=0.01, | |
paramwise_cfg=dict(custom_keys={'absolute_pos_embed': dict(decay_mult=0.), | |
'relative_position_bias_table': dict(decay_mult=0.), | |
'norm': dict(decay_mult=0.)})) | |
lr_config = dict(_delete_=True, policy='poly', | |
warmup='linear', | |
warmup_iters=1500, | |
warmup_ratio=1e-6, | |
power=1.0, min_lr=0.0, by_epoch=False) | |
data=dict(samples_per_gpu=2) |