def test_conv2(self):
x = torch.rand(math.floor(torch.uniform(50, 100)), math.floor(torch.uniform(50, 100)))
k = torch.rand(math.floor(torch.uniform(10, 20)), math.floor(torch.uniform(10, 20)))
imvc = torch.conv2(x, k)
imvc2 = torch.conv2(x, k, 'V')
imfc = torch.conv2(x, k, 'F')
ki = k.clone()
ks = k.storage()
kis = ki.storage()
for i in range(ks.size()-1, 0, -1):
kis[ks.size()-i+1] = ks[i]
#for i=ks.size(), 1, -1 do kis[ks.size()-i+1]=ks[i] end
imvx = torch.xcorr2(x, ki)
imvx2 = torch.xcorr2(x, ki, 'V')
imfx = torch.xcorr2(x, ki, 'F')
self.assertEqual(imvc, imvc2, 0, 'torch.conv2')
self.assertEqual(imvc, imvx, 0, 'torch.conv2')
self.assertEqual(imvc, imvx2, 0, 'torch.conv2')
self.assertEqual(imfc, imfx, 0, 'torch.conv2')
self.assertLessEqual(math.abs(x.dot(x) - torch.xcorr2(x, x)[0][0]), 1e-10, 'torch.conv2')
xx = torch.Tensor(2, x.size(1), x.size(2))
xx[1].copy_(x)
xx[2].copy_(x)
kk = torch.Tensor(2, k.size(1), k.size(2))
kk[1].copy_(k)
kk[2].copy_(k)
immvc = torch.conv2(xx, kk)
immvc2 = torch.conv2(xx, kk, 'V')
immfc = torch.conv2(xx, kk, 'F')
self.assertEqual(immvc[0], immvc[1], 0, 'torch.conv2')
self.assertEqual(immvc[0], imvc, 0, 'torch.conv2')
self.assertEqual(immvc2[0], imvc2, 0, 'torch.conv2')
self.assertEqual(immfc[0], immfc[1], 0, 'torch.conv2')
self.assertEqual(immfc[0], imfc, 0, 'torch.conv2')
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