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