def test_3D_simple_(self):
x = torch.autograd.Variable(torch.rand(1,3,20, 64,15))
model = bb.ResBlock(in_channels=3, out_channels=3, dim=3)
xx = model(x)
out_size = xx.size()
self.assertEqual(list(out_size), [1,3, 20, 64, 15])
def test_2D_simple_3(self):
x = torch.autograd.Variable(torch.rand(1,3,64,64))
model = bb.ResBlock(in_channels=3, out_channels=6, dim=2, size=4)
xx = model(x)
out_size = xx.size()
self.assertEqual(list(out_size), [1,6, 64, 64])
def test_3D_simple_6(self):
x = torch.autograd.Variable(torch.rand(1,6,64,64, 20))
model = bb.ResBlock(in_channels=6, batchnorm=False, out_channels=6, dim=3, size=4,
force_skip_op=True, activated=False)
xx = model(x)
out_size = xx.size()
self.assertEqual(list(out_size), [1,6, 64, 64, 20])