mmpretrain/tests/test_models/test_selfsup/test_beit.py

29 lines
695 B
Python

# Copyright (c) OpenMMLab. All rights reserved.
import platform
import pytest
import torch
from mmpretrain.models import BEiTPretrainViT
backbone = dict(
arch='base',
patch_size=16,
drop_path_rate=0.1,
final_norm=True,
layer_scale_init_value=0.1,
)
@pytest.mark.skipif(platform.system() == 'Windows', reason='Windows mem limit')
def test_beit_pretrain_vit():
beit_backbone = BEiTPretrainViT(**backbone)
beit_backbone.init_weights()
fake_inputs = torch.randn((2, 3, 224, 224))
fake_mask = torch.zeros((2, 196))
fake_mask[:, 75:150] = 1
fake_outputs = beit_backbone(fake_inputs, fake_mask)
assert list(fake_outputs[0].shape) == [2, 197, 768]