25 lines
670 B
Python
25 lines
670 B
Python
|
_base_ = [
|
||
|
|
'../_base_/models/convnext/convnext-base.py',
|
||
|
|
'../_base_/datasets/imagenet21k_bs128.py',
|
||
|
|
'../_base_/schedules/imagenet_bs1024_adamw_swin.py',
|
||
|
|
'../_base_/default_runtime.py',
|
||
|
|
]
|
||
|
|
|
||
|
|
# model setting
|
||
|
|
model = dict(head=dict(num_classes=21841))
|
||
|
|
|
||
|
|
# dataset setting
|
||
|
|
data_preprocessor = dict(num_classes=21841)
|
||
|
|
train_dataloader = dict(batch_size=128)
|
||
|
|
|
||
|
|
# schedule setting
|
||
|
|
optim_wrapper = dict(
|
||
|
|
optimizer=dict(lr=4e-3),
|
||
|
|
clip_grad=dict(max_norm=5.0),
|
||
|
|
)
|
||
|
|
|
||
|
|
# NOTE: `auto_scale_lr` is for automatically scaling LR
|
||
|
|
# based on the actual training batch size.
|
||
|
|
# base_batch_size = (32 GPUs) x (128 samples per GPU)
|
||
|
|
auto_scale_lr = dict(base_batch_size=4096)
|