def test_conv3d():
inp = tensor(np.ones((256, ), dtype=np.float32).reshape(2, 2, 4, 4, 4))
weight = tensor(np.ones((48, ), dtype=np.float32).reshape(3, 2, 2, 2, 2))
out = F.conv3d(inp, weight, None, 2, 0, 1, 1)
print(out.numpy().shape)
np.testing.assert_equal(out.numpy(),
np.ones((2, 3, 2, 2, 2), dtype=np.float32) * 16)
def test_conv3d_zero_stride_numpy_array():
inp = np.random.randn(3, 224, 224, 224).astype(np.float32)
inp = inp[np.newaxis, :]
inp = tensor(inp, dtype=np.float32)
weight = tensor(np.random.randn(16, 3, 3, 3, 3), dtype=np.float32)
out = F.conv3d(inp, weight, None, (2, 2, 2), (3, 3, 3), (1, 1, 1), 1)
out.numpy()
def test_conv3d():
inp = tensor(np.ones((2, 2, 4, 4, 4), dtype=np.float32))
weight = tensor(np.ones((3, 2, 2, 2, 2), dtype=np.float32))
out = F.conv3d(inp, weight, None, 2, 0, 1, 1)
np.testing.assert_equal(out.numpy(),
np.ones((2, 3, 2, 2, 2), dtype=np.float32) * 16)