mmpretrain/configs/eva02/eva02-tiny-p14_in1k.py

32 lines
837 B
Python

_base_ = [
'../_base_/datasets/imagenet_bs16_eva_336.py',
'../_base_/schedules/imagenet_bs2048_AdamW.py',
'../_base_/default_runtime.py'
]
model = dict(
type='ImageClassifier',
backbone=dict(
type='ViTEVA02',
arch='t',
img_size=336,
patch_size=14,
final_norm=False,
out_type='avg_featmap'),
neck=None,
head=dict(
type='LinearClsHead',
num_classes=1000,
in_channels=192,
loss=dict(
type='LabelSmoothLoss', label_smooth_val=0.1, mode='original'),
),
init_cfg=[
dict(type='TruncNormal', layer='Linear', std=.02),
dict(type='Constant', layer='LayerNorm', val=1., bias=0.),
],
train_cfg=dict(augments=[
dict(type='Mixup', alpha=0.8),
dict(type='CutMix', alpha=1.0)
]))