import sys import pytest np = pytest.importorskip("numpy") eigen_tensor = pytest.importorskip("pybind11_tests.eigen_tensor") submodules = [eigen_tensor.c_style, eigen_tensor.f_style] try: from pybind11_tests import eigen_tensor_avoid_stl_array as avoid submodules += [avoid.c_style, avoid.f_style] except ImportError: pass tensor_ref = np.empty((3, 5, 2), dtype=np.int64) for i in range(tensor_ref.shape[0]): for j in range(tensor_ref.shape[1]): for k in range(tensor_ref.shape[2]): tensor_ref[i, j, k] = i * (5 * 2) + j * 2 + k indices = (2, 3, 1) @pytest.fixture(autouse=True) def cleanup(): for module in submodules: module.setup() yield for module in submodules: assert module.is_ok() def test_import_avoid_stl_array(): pytest.importorskip("pybind11_tests.eigen_tensor_avoid_stl_array") assert len(submodules) == 4 def assert_equal_tensor_ref(mat, writeable=True, modified=None): assert mat.flags.writeable == writeable copy = np.array(tensor_ref) if modified is not None: copy[indices] = modified np.testing.assert_array_equal(mat, copy) @pytest.mark.parametrize("m", submodules) @pytest.mark.parametrize("member_name", ["member", "member_view"]) def test_reference_internal(m, member_name): if not hasattr(sys, "getrefcount"): pytest.skip("No reference counting") foo = m.CustomExample() counts = sys.getrefcount(foo) mem = getattr(foo, member_name) assert_equal_tensor_ref(mem, writeable=False) new_counts = sys.getrefcount(foo) assert new_counts == counts + 1 assert_equal_tensor_ref(mem, writeable=False) del mem assert sys.getrefcount(foo) == counts assert_equal_funcs = [ "copy_tensor", "copy_fixed_tensor", "copy_const_tensor", "move_tensor_copy", "move_fixed_tensor_copy", "take_tensor", "take_fixed_tensor", "reference_tensor", "reference_tensor_v2", "reference_fixed_tensor", "reference_view_of_tensor", "reference_view_of_tensor_v3", "reference_view_of_tensor_v5", "reference_view_of_fixed_tensor", ] assert_equal_const_funcs = [ "reference_view_of_tensor_v2", "reference_view_of_tensor_v4", "reference_view_of_tensor_v6", "reference_const_tensor", "reference_const_tensor_v2", ] @pytest.mark.parametrize("m", submodules) @pytest.mark.parametrize("func_name", assert_equal_funcs + assert_equal_const_funcs) def test_convert_tensor_to_py(m, func_name): writeable = func_name in assert_equal_funcs assert_equal_tensor_ref(getattr(m, func_name)(), writeable=writeable) @pytest.mark.parametrize("m", submodules) def test_bad_cpp_to_python_casts(m): with pytest.raises( RuntimeError, match="Cannot use reference internal when there is no parent" ): m.reference_tensor_internal() with pytest.raises(RuntimeError, match="Cannot move from a constant reference"): m.move_const_tensor() with pytest.raises( RuntimeError, match="Cannot take ownership of a const reference" ): m.take_const_tensor() with pytest.raises( RuntimeError, match="Invalid return_value_policy for Eigen Map type, must be either reference or reference_internal", ): m.take_view_tensor() @pytest.mark.parametrize("m", submodules) def test_bad_python_to_cpp_casts(m): with pytest.raises( TypeError, match=r"^round_trip_tensor\(\): incompatible function arguments" ): m.round_trip_tensor(np.zeros((2, 3))) with pytest.raises(TypeError, match=r"^Cannot cast array data from dtype"): m.round_trip_tensor(np.zeros(dtype=np.str_, shape=(2, 3, 1))) with pytest.raises( TypeError, match=r"^round_trip_tensor_noconvert\(\): incompatible function arguments", ): m.round_trip_tensor_noconvert(tensor_ref) assert_equal_tensor_ref( m.round_trip_tensor_noconvert(tensor_ref.astype(np.float64)) ) if m.needed_options == "F": bad_options = "C" else: bad_options = "F" # Shape, dtype and the order need to be correct for a TensorMap cast with pytest.raises( TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments" ): m.round_trip_view_tensor( np.zeros((3, 5, 2), dtype=np.float64, order=bad_options) ) with pytest.raises( TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments" ): m.round_trip_view_tensor( np.zeros((3, 5, 2), dtype=np.float32, order=m.needed_options) ) with pytest.raises( TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments" ): m.round_trip_view_tensor( np.zeros((3, 5), dtype=np.float64, order=m.needed_options) ) with pytest.raises( TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments" ): temp = np.zeros((3, 5, 2), dtype=np.float64, order=m.needed_options) m.round_trip_view_tensor( temp[:, ::-1, :], ) with pytest.raises( TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments" ): temp = np.zeros((3, 5, 2), dtype=np.float64, order=m.needed_options) temp.setflags(write=False) m.round_trip_view_tensor(temp) @pytest.mark.parametrize("m", submodules) def test_references_actually_refer(m): a = m.reference_tensor() temp = a[indices] a[indices] = 100 assert_equal_tensor_ref(m.copy_const_tensor(), modified=100) a[indices] = temp assert_equal_tensor_ref(m.copy_const_tensor()) a = m.reference_view_of_tensor() a[indices] = 100 assert_equal_tensor_ref(m.copy_const_tensor(), modified=100) a[indices] = temp assert_equal_tensor_ref(m.copy_const_tensor()) @pytest.mark.parametrize("m", submodules) def test_round_trip(m): assert_equal_tensor_ref(m.round_trip_tensor(tensor_ref)) with pytest.raises(TypeError, match="^Cannot cast array data from"): assert_equal_tensor_ref(m.round_trip_tensor2(tensor_ref)) assert_equal_tensor_ref(m.round_trip_tensor2(np.array(tensor_ref, dtype=np.int32))) assert_equal_tensor_ref(m.round_trip_fixed_tensor(tensor_ref)) assert_equal_tensor_ref(m.round_trip_aligned_view_tensor(m.reference_tensor())) copy = np.array(tensor_ref, dtype=np.float64, order=m.needed_options) assert_equal_tensor_ref(m.round_trip_view_tensor(copy)) assert_equal_tensor_ref(m.round_trip_view_tensor_ref(copy)) assert_equal_tensor_ref(m.round_trip_view_tensor_ptr(copy)) copy.setflags(write=False) assert_equal_tensor_ref(m.round_trip_const_view_tensor(copy)) np.testing.assert_array_equal( tensor_ref[:, ::-1, :], m.round_trip_tensor(tensor_ref[:, ::-1, :]) ) assert m.round_trip_rank_0(np.float64(3.5)) == 3.5 assert m.round_trip_rank_0(3.5) == 3.5 with pytest.raises( TypeError, match=r"^round_trip_rank_0_noconvert\(\): incompatible function arguments", ): m.round_trip_rank_0_noconvert(np.float64(3.5)) with pytest.raises( TypeError, match=r"^round_trip_rank_0_noconvert\(\): incompatible function arguments", ): m.round_trip_rank_0_noconvert(3.5) with pytest.raises( TypeError, match=r"^round_trip_rank_0_view\(\): incompatible function arguments" ): m.round_trip_rank_0_view(np.float64(3.5)) with pytest.raises( TypeError, match=r"^round_trip_rank_0_view\(\): incompatible function arguments" ): m.round_trip_rank_0_view(3.5) @pytest.mark.parametrize("m", submodules) def test_round_trip_references_actually_refer(m): # Need to create a copy that matches the type on the C side copy = np.array(tensor_ref, dtype=np.float64, order=m.needed_options) a = m.round_trip_view_tensor(copy) temp = a[indices] a[indices] = 100 assert_equal_tensor_ref(copy, modified=100) a[indices] = temp assert_equal_tensor_ref(copy) @pytest.mark.parametrize("m", submodules) def test_doc_string(m, doc): assert ( doc(m.copy_tensor) == "copy_tensor() -> numpy.ndarray[numpy.float64[?, ?, ?]]" ) assert ( doc(m.copy_fixed_tensor) == "copy_fixed_tensor() -> numpy.ndarray[numpy.float64[3, 5, 2]]" ) assert ( doc(m.reference_const_tensor) == "reference_const_tensor() -> numpy.ndarray[numpy.float64[?, ?, ?]]" ) order_flag = f"flags.{m.needed_options.lower()}_contiguous" assert doc(m.round_trip_view_tensor) == ( f"round_trip_view_tensor(arg0: numpy.ndarray[numpy.float64[?, ?, ?], flags.writeable, {order_flag}])" + f" -> numpy.ndarray[numpy.float64[?, ?, ?], flags.writeable, {order_flag}]" ) assert doc(m.round_trip_const_view_tensor) == ( f"round_trip_const_view_tensor(arg0: numpy.ndarray[numpy.float64[?, ?, ?], {order_flag}])" + " -> numpy.ndarray[numpy.float64[?, ?, ?]]" )