def test_view_of_view_modification():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata[0, :][:, 5:].X = np.ones(5)
    assert np.all(adata.X[0, 5:] == np.ones(5))
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2))
    assert np.all(adata.X[1:3, 1:3] == np.ones((2, 2)))

    adata.X = sparse.csr_matrix(adata.X)
    adata[0, :][:, 5:].X = np.ones(5) * 2
    assert np.all(asarray(adata.X)[0, 5:] == np.ones(5) * 2)
    adata[[1, 2], :][:, [1, 2]].X = np.ones((2, 2)) * 2
    assert np.all(asarray(adata.X)[1:3, 1:3] == np.ones((2, 2)) * 2)
def test_if_likely():
    ib = tvm.tir.ir_builder.create()
    A = ib.pointer("float32", name="A")
    C = ib.pointer("float32", name="C")
    n = te.size_var("n")
    tx = te.thread_axis("threadIdx.x")
    ty = te.thread_axis("threadIdx.y")
    ib.scope_attr(tx, "thread_extent", 32)
    ib.scope_attr(ty, "thread_extent", 32)
    with ib.if_scope(ib.likely(tx * 32 + ty < n)):
        with ib.if_scope(ib.likely(tx * 32 + ty < n)):
            A[tx] = C[tx * 32 + ty]
    body = ib.get()
    mod = tvm.IRModule.from_expr(tvm.tir.PrimFunc([A, C, n], body))
    body = tvm.tir.transform.Simplify()(mod)["main"].body
    assert isinstance(body.body.body, tvm.tir.IfThenElse)
    assert not isinstance(body.body.body.then_case, tvm.tir.IfThenElse)