mmselfsup/tests/test_models/test_algorithms/test_simmim.py

29 lines
868 B
Python

# Copyright (c) OpenMMLab. All rights reserved.
import platform
import pytest
import torch
from mmselfsup.models.algorithms import SimMIM
@pytest.mark.skipif(platform.system() == 'Windows', reason='Windows mem limit')
def test_simmim():
# model config
model_config = dict(
backbone=dict(
type='SimMIMSwinTransformer',
arch='B',
img_size=192,
stage_cfgs=dict(block_cfgs=dict(window_size=6))),
neck=dict(
type='SimMIMNeck', in_channels=128 * 2**3, encoder_stride=32),
head=dict(type='SimMIMHead', patch_size=4, encoder_in_channels=3))
model = SimMIM(**model_config)
fake_inputs = torch.rand((2, 3, 192, 192))
fake_masks = torch.rand((2, 48, 48))
outputs = model.forward_train([fake_inputs, fake_masks])
assert isinstance(outputs['loss'], torch.Tensor)