# Copyright (c) OpenMMLab. All rights reserved. | |
import pytest | |
import torch | |
from mmdet.models.utils import ConvUpsample | |
def test_conv_upsample(num_layers): | |
num_upsample = num_layers if num_layers > 0 else 0 | |
num_layers = num_layers if num_layers > 0 else 1 | |
layer = ConvUpsample( | |
10, | |
5, | |
num_layers=num_layers, | |
num_upsample=num_upsample, | |
conv_cfg=None, | |
norm_cfg=None) | |
size = 5 | |
x = torch.randn((1, 10, size, size)) | |
size = size * pow(2, num_upsample) | |
x = layer(x) | |
assert x.shape[-2:] == (size, size) | |