mirror of https://github.com/open-mmlab/mmcv.git
42 lines
1.3 KiB
Python
42 lines
1.3 KiB
Python
import pytest
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import torch
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from torch.autograd import gradcheck, gradgradcheck
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class TestUpFirDn2d(object):
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"""Unit test for UpFirDn2d.
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Here, we just test the basic case of upsample version. More gerneal tests
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will be included in other unit test for UpFirDnUpsample and
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UpFirDnDownSample modules.
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"""
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@classmethod
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def setup_class(cls):
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kernel_1d = torch.tensor([1., 3., 3., 1.])
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cls.kernel = kernel_1d[:, None] * kernel_1d[None, :]
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cls.kernel = cls.kernel / cls.kernel.sum()
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cls.factor = 2
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pad = cls.kernel.shape[0] - cls.factor
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cls.pad = ((pad + 1) // 2 + cls.factor - 1, pad // 2)
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cls.input_tensor = torch.randn((2, 3, 4, 4), requires_grad=True)
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@pytest.mark.skipif(not torch.cuda.is_available(), reason='requires cuda')
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def test_upfirdn2d(self):
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from mmcv.ops import upfirdn2d
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gradcheck(
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upfirdn2d,
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(self.input_tensor.cuda(), self.kernel.type_as(
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self.input_tensor).cuda(), self.factor, 1, self.pad),
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eps=1e-4,
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atol=1e-3)
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gradgradcheck(
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upfirdn2d,
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(self.input_tensor.cuda(), self.kernel.type_as(
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self.input_tensor).cuda(), self.factor, 1, self.pad),
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eps=1e-4,
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atol=1e-3)
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