def test_deepcopy_subset(adata, spmat: type):
    adata.obsp["arr"] = np.zeros((adata.n_obs, adata.n_obs))
    adata.obsp["spmat"] = spmat((adata.n_obs, adata.n_obs))

    adata = deepcopy(adata[:10].copy())

    assert isinstance(adata.obsp["arr"], np.ndarray)
    assert not isinstance(adata.obsp["arr"], ArrayView)
    np.testing.assert_array_equal(adata.obsp["arr"].shape, (10, 10))

    assert isinstance(adata.obsp["spmat"], spmat)
    assert not isinstance(
        adata.obsp["spmat"],
        SparseCSRView if spmat is sparse.csr_matrix else SparseCSCView,
    )
    np.testing.assert_array_equal(adata.obsp["spmat"].shape, (10, 10))
def test_thread_extent_simplify():
    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", n)
    ib.scope_attr(tx, "thread_extent", n)
    ib.scope_attr(ty, "thread_extent", 1)
    with ib.if_scope(tx + ty < 12):
        A[tx] = C[tx + ty]
    body = tvm.tir.LetStmt(n, 10, 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.body, tvm.tir.Store)