mirror of
https://github.com/open-mmlab/mmselfsup.git
synced 2025-06-03 14:59:38 +08:00
48 lines
1.2 KiB
Python
48 lines
1.2 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
|
|
import pytest
|
|
import torch
|
|
|
|
from mmselfsup.models.algorithms import ODC
|
|
|
|
num_classes = 5
|
|
backbone = dict(
|
|
type='ResNet',
|
|
depth=50,
|
|
in_channels=3,
|
|
out_indices=[4], # 0: conv-1, x: stage-x
|
|
norm_cfg=dict(type='BN'))
|
|
neck = dict(
|
|
type='ODCNeck',
|
|
in_channels=2048,
|
|
hid_channels=4,
|
|
out_channels=4,
|
|
with_avg_pool=True)
|
|
head = dict(
|
|
type='ClsHead',
|
|
with_avg_pool=False,
|
|
in_channels=4,
|
|
num_classes=num_classes)
|
|
memory_bank = dict(
|
|
type='ODCMemory',
|
|
length=8,
|
|
feat_dim=4,
|
|
momentum=0.5,
|
|
num_classes=num_classes,
|
|
min_cluster=2,
|
|
debug=False)
|
|
|
|
|
|
@pytest.mark.skipif(
|
|
not torch.cuda.is_available(), reason='CUDA is not available.')
|
|
def test_odc():
|
|
with pytest.raises(AssertionError):
|
|
alg = ODC(backbone=backbone, neck=neck, head=head, memory_bank=None)
|
|
with pytest.raises(AssertionError):
|
|
alg = ODC(
|
|
backbone=backbone, neck=neck, head=None, memory_bank=memory_bank)
|
|
|
|
alg = ODC(backbone=backbone, neck=neck, head=head, memory_bank=memory_bank)
|
|
fake_input = torch.randn((16, 3, 224, 224))
|
|
fake_backbone_out = alg.extract_feat(fake_input)
|
|
assert fake_backbone_out[0].size() == torch.Size([16, 2048, 7, 7])
|