mmclassification/configs/efficientformer/efficientformer-l3_8xb128_i...

25 lines
770 B
Python

_base_ = [
'../_base_/datasets/imagenet_bs128_poolformer_small_224.py',
'../_base_/schedules/imagenet_bs1024_adamw_swin.py',
'../_base_/default_runtime.py',
]
model = dict(
type='ImageClassifier',
backbone=dict(
type='EfficientFormer',
arch='l3',
drop_path_rate=0,
init_cfg=[
dict(
type='TruncNormal',
layer=['Conv2d', 'Linear'],
std=.02,
bias=0.),
dict(type='Constant', layer=['GroupNorm'], val=1., bias=0.),
dict(type='Constant', layer=['LayerScale'], val=1e-5)
]),
neck=dict(type='GlobalAveragePooling', dim=1),
head=dict(
type='EfficientFormerClsHead', in_channels=512, num_classes=1000))