File size: 9,414 Bytes
f5bb0c0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 |
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:
import eigen_tensor_avoid_stl_array as avoid
submodules += [avoid.c_style, avoid.f_style]
except ImportError as e:
# Ensure config, build, toolchain, etc. issues are not masked here:
msg = (
"import eigen_tensor_avoid_stl_array FAILED, while "
"import pybind11_tests.eigen_tensor succeeded. "
"Please ensure that "
"test_eigen_tensor.cpp & "
"eigen_tensor_avoid_stl_array.cpp "
"are built together (or both are not built if Eigen is not available)."
)
raise RuntimeError(msg) from e
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("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))
)
bad_options = "C" if m.needed_options == "F" else "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)
)
temp = np.zeros((3, 5, 2), dtype=np.float64, order=m.needed_options)
with pytest.raises(
TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments"
):
m.round_trip_view_tensor(
temp[:, ::-1, :],
)
temp = np.zeros((3, 5, 2), dtype=np.float64, order=m.needed_options)
temp.setflags(write=False)
with pytest.raises(
TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments"
):
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[?, ?, ?]]"
)
|