mmpretrain/tests/test_models/test_selfsup/test_simmim.py

22 lines
639 B
Python

# Copyright (c) OpenMMLab. All rights reserved.
import platform
import pytest
import torch
from mmpretrain.models import SimMIMSwinTransformer
backbone = dict(
arch='B', img_size=192, stage_cfgs=dict(block_cfgs=dict(window_size=6)))
@pytest.mark.skipif(platform.system() == 'Windows', reason='Windows mem limit')
def test_cae_vit():
simmim_backbone = SimMIMSwinTransformer(**backbone)
simmim_backbone.init_weights()
fake_inputs = torch.randn((2, 3, 192, 192))
fake_mask = torch.rand((2, 48, 48))
fake_outputs = simmim_backbone(fake_inputs, fake_mask)[0]
assert list(fake_outputs.shape) == [2, 1024, 6, 6]