mirror of
https://github.com/open-mmlab/mmselfsup.git
synced 2025-06-03 14:59:38 +08:00
55 lines
1.4 KiB
Python
55 lines
1.4 KiB
Python
|
# Copyright (c) OpenMMLab. All rights reserved.
|
||
|
|
import pytest
|
||
|
|
import torch
|
||
|
|
|
||
|
|
from mmselfsup.models import MoCoV3
|
||
|
|
|
||
|
|
backbone = dict(
|
||
|
|
type='VisionTransformer',
|
||
|
|
arch='mocov3-small', # embed_dim = 384
|
||
|
|
img_size=224,
|
||
|
|
patch_size=16,
|
||
|
|
stop_grad_conv1=True)
|
||
|
|
neck = dict(
|
||
|
|
type='NonLinearNeck',
|
||
|
|
in_channels=384,
|
||
|
|
hid_channels=8,
|
||
|
|
out_channels=8,
|
||
|
|
num_layers=2,
|
||
|
|
with_bias=False,
|
||
|
|
with_last_bn=True,
|
||
|
|
with_last_bn_affine=False,
|
||
|
|
with_last_bias=False,
|
||
|
|
with_avg_pool=False,
|
||
|
|
vit_backbone=True)
|
||
|
|
head = dict(
|
||
|
|
type='MoCoV3Head',
|
||
|
|
predictor=dict(
|
||
|
|
type='NonLinearNeck',
|
||
|
|
in_channels=8,
|
||
|
|
hid_channels=8,
|
||
|
|
out_channels=8,
|
||
|
|
num_layers=2,
|
||
|
|
with_bias=False,
|
||
|
|
with_last_bn=True,
|
||
|
|
with_last_bn_affine=False,
|
||
|
|
with_last_bias=False,
|
||
|
|
with_avg_pool=False),
|
||
|
|
temperature=0.2)
|
||
|
|
|
||
|
|
|
||
|
|
def test_mocov3():
|
||
|
|
with pytest.raises(AssertionError):
|
||
|
|
alg = MoCoV3(backbone=backbone, neck=None, head=head)
|
||
|
|
with pytest.raises(AssertionError):
|
||
|
|
alg = MoCoV3(backbone=backbone, neck=neck, head=None)
|
||
|
|
|
||
|
|
alg = MoCoV3(backbone, neck, head)
|
||
|
|
alg.init_weights()
|
||
|
|
alg.momentum_update()
|
||
|
|
|
||
|
|
fake_input = torch.randn((16, 3, 224, 224))
|
||
|
|
fake_backbone_out = alg.extract_feat(fake_input)
|
||
|
|
assert fake_backbone_out[0][0].size() == torch.Size([16, 384, 14, 14])
|
||
|
|
assert fake_backbone_out[0][1].size() == torch.Size([16, 384])
|