derek/gem5
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

ext: Update pybind11 to version 2.6.2.

Browse Source 
This should help reduce warning spew when building with newer compilers.
The pybind11::module type has been renamed pybind11::module_ to avoid
conflicts with c++20 modules, according to the pybind11 changelog, so
this CL also updates gem5 source to use the new type. There is
supposedly an alias pybind11::module which is for compatibility, but we
still get linker errors without changing to pybind11::module_.

Change-Id: I0acb36215b33e3a713866baec43f5af630c356ee
Reviewed-on: https://gem5-review.googlesource.com/c/public/gem5/+/40255
Maintainer: Bobby R. Bruce <bbruce@ucdavis.edu>
Reviewed-by: Bobby R. Bruce <bbruce@ucdavis.edu>
Tested-by: kokoro <noreply+kokoro@google.com>
This commit is contained in:
Gabe Black
2021-01-31 06:07:28 -08:00
parent f0924fc39b
commit c4aaf373aa
227 changed files with 13789 additions and 4474 deletions
Download Patch File Download Diff File Expand all files Collapse all files

292
ext/pybind11/tests/test_numpy_array.py
View File

@@ -1,10 +1,11 @@
# -*- coding: utf-8 -*-
import pytest
import env # noqa: F401
from pybind11_tests import numpy_array as m
pytestmark = pytest.requires_numpy
with pytest.suppress(ImportError):
import numpy as np
np = pytest.importorskip("numpy")
def test_dtypes():
@@ -18,33 +19,36 @@ def test_dtypes():
print(check)
assert check.numpy == check.pybind11, check
if check.numpy.num != check.pybind11.num:
print("NOTE: typenum mismatch for {}: {} != {}".format(
check, check.numpy.num, check.pybind11.num))
print(
"NOTE: typenum mismatch for {}: {} != {}".format(
check, check.numpy.num, check.pybind11.num
)
)
@pytest.fixture(scope='function')
@pytest.fixture(scope="function")
def arr():
return np.array([[1, 2, 3], [4, 5, 6]], '=u2')
return np.array([[1, 2, 3], [4, 5, 6]], "=u2")
def test_array_attributes():
a = np.array(0, 'f8')
a = np.array(0, "f8")
assert m.ndim(a) == 0
assert all(m.shape(a) == [])
assert all(m.strides(a) == [])
with pytest.raises(IndexError) as excinfo:
m.shape(a, 0)
assert str(excinfo.value) == 'invalid axis: 0 (ndim = 0)'
assert str(excinfo.value) == "invalid axis: 0 (ndim = 0)"
with pytest.raises(IndexError) as excinfo:
m.strides(a, 0)
assert str(excinfo.value) == 'invalid axis: 0 (ndim = 0)'
assert str(excinfo.value) == "invalid axis: 0 (ndim = 0)"
assert m.writeable(a)
assert m.size(a) == 1
assert m.itemsize(a) == 8
assert m.nbytes(a) == 8
assert m.owndata(a)
a = np.array([[1, 2, 3], [4, 5, 6]], 'u2').view()
a = np.array([[1, 2, 3], [4, 5, 6]], "u2").view()
a.flags.writeable = False
assert m.ndim(a) == 2
assert all(m.shape(a) == [2, 3])
@@ -55,10 +59,10 @@ def test_array_attributes():
assert m.strides(a, 1) == 2
with pytest.raises(IndexError) as excinfo:
m.shape(a, 2)
assert str(excinfo.value) == 'invalid axis: 2 (ndim = 2)'
assert str(excinfo.value) == "invalid axis: 2 (ndim = 2)"
with pytest.raises(IndexError) as excinfo:
m.strides(a, 2)
assert str(excinfo.value) == 'invalid axis: 2 (ndim = 2)'
assert str(excinfo.value) == "invalid axis: 2 (ndim = 2)"
assert not m.writeable(a)
assert m.size(a) == 6
assert m.itemsize(a) == 2
@@ -66,7 +70,9 @@ def test_array_attributes():
assert not m.owndata(a)
@pytest.mark.parametrize('args, ret', [([], 0), ([0], 0), ([1], 3), ([0, 1], 1), ([1, 2], 5)])
@pytest.mark.parametrize(
"args, ret", [([], 0), ([0], 0), ([1], 3), ([0, 1], 1), ([1, 2], 5)]
)
def test_index_offset(arr, args, ret):
assert m.index_at(arr, *args) == ret
assert m.index_at_t(arr, *args) == ret
@@ -75,31 +81,46 @@ def test_index_offset(arr, args, ret):
def test_dim_check_fail(arr):
for func in (m.index_at, m.index_at_t, m.offset_at, m.offset_at_t, m.data, m.data_t,
m.mutate_data, m.mutate_data_t):
for func in (
m.index_at,
m.index_at_t,
m.offset_at,
m.offset_at_t,
m.data,
m.data_t,
m.mutate_data,
m.mutate_data_t,
):
with pytest.raises(IndexError) as excinfo:
func(arr, 1, 2, 3)
assert str(excinfo.value) == 'too many indices for an array: 3 (ndim = 2)'
assert str(excinfo.value) == "too many indices for an array: 3 (ndim = 2)"
@pytest.mark.parametrize('args, ret',
[([], [1, 2, 3, 4, 5, 6]),
([1], [4, 5, 6]),
([0, 1], [2, 3, 4, 5, 6]),
([1, 2], [6])])
@pytest.mark.parametrize(
"args, ret",
[
([], [1, 2, 3, 4, 5, 6]),
([1], [4, 5, 6]),
([0, 1], [2, 3, 4, 5, 6]),
([1, 2], [6]),
],
)
def test_data(arr, args, ret):
from sys import byteorder
assert all(m.data_t(arr, *args) == ret)
assert all(m.data(arr, *args)[(0 if byteorder == 'little' else 1)::2] == ret)
assert all(m.data(arr, *args)[(1 if byteorder == 'little' else 0)::2] == 0)
assert all(m.data(arr, *args)[(0 if byteorder == "little" else 1) :: 2] == ret)
assert all(m.data(arr, *args)[(1 if byteorder == "little" else 0) :: 2] == 0)
@pytest.mark.parametrize('dim', [0, 1, 3])
@pytest.mark.parametrize("dim", [0, 1, 3])
def test_at_fail(arr, dim):
for func in m.at_t, m.mutate_at_t:
with pytest.raises(IndexError) as excinfo:
func(arr, *([0] * dim))
assert str(excinfo.value) == 'index dimension mismatch: {} (ndim = 2)'.format(dim)
assert str(excinfo.value) == "index dimension mismatch: {} (ndim = 2)".format(
dim
)
def test_at(arr):
@@ -112,10 +133,14 @@ def test_at(arr):
def test_mutate_readonly(arr):
arr.flags.writeable = False
for func, args in (m.mutate_data, ()), (m.mutate_data_t, ()), (m.mutate_at_t, (0, 0)):
for func, args in (
(m.mutate_data, ()),
(m.mutate_data_t, ()),
(m.mutate_at_t, (0, 0)),
):
with pytest.raises(ValueError) as excinfo:
func(arr, *args)
assert str(excinfo.value) == 'array is not writeable'
assert str(excinfo.value) == "array is not writeable"
def test_mutate_data(arr):
@@ -133,14 +158,22 @@ def test_mutate_data(arr):
def test_bounds_check(arr):
for func in (m.index_at, m.index_at_t, m.data, m.data_t,
m.mutate_data, m.mutate_data_t, m.at_t, m.mutate_at_t):
for func in (
m.index_at,
m.index_at_t,
m.data,
m.data_t,
m.mutate_data,
m.mutate_data_t,
m.at_t,
m.mutate_at_t,
):
with pytest.raises(IndexError) as excinfo:
func(arr, 2, 0)
assert str(excinfo.value) == 'index 2 is out of bounds for axis 0 with size 2'
assert str(excinfo.value) == "index 2 is out of bounds for axis 0 with size 2"
with pytest.raises(IndexError) as excinfo:
func(arr, 0, 4)
assert str(excinfo.value) == 'index 4 is out of bounds for axis 1 with size 3'
assert str(excinfo.value) == "index 4 is out of bounds for axis 1 with size 3"
def test_make_c_f_array():
@@ -162,10 +195,11 @@ def test_make_empty_shaped_array():
def test_wrap():
def assert_references(a, b, base=None):
from distutils.version import LooseVersion
if base is None:
base = a
assert a is not b
assert a.__array_interface__['data'][0] == b.__array_interface__['data'][0]
assert a.__array_interface__["data"][0] == b.__array_interface__["data"][0]
assert a.shape == b.shape
assert a.strides == b.strides
assert a.flags.c_contiguous == b.flags.c_contiguous
@@ -188,12 +222,12 @@ def test_wrap():
a2 = m.wrap(a1)
assert_references(a1, a2)
a1 = np.array([[1, 2], [3, 4]], dtype=np.float32, order='F')
a1 = np.array([[1, 2], [3, 4]], dtype=np.float32, order="F")
assert a1.flags.owndata and a1.base is None
a2 = m.wrap(a1)
assert_references(a1, a2)
a1 = np.array([[1, 2], [3, 4]], dtype=np.float32, order='C')
a1 = np.array([[1, 2], [3, 4]], dtype=np.float32, order="C")
a1.flags.writeable = False
a2 = m.wrap(a1)
assert_references(a1, a2)
@@ -223,11 +257,14 @@ def test_numpy_view(capture):
assert np.all(ac_view_1 == np.array([1, 2], dtype=np.int32))
del ac
pytest.gc_collect()
assert capture == """
assert (
capture
== """
ArrayClass()
ArrayClass::numpy_view()
ArrayClass::numpy_view()
"""
)
ac_view_1[0] = 4
ac_view_1[1] = 3
assert ac_view_2[0] == 4
@@ -237,12 +274,14 @@ def test_numpy_view(capture):
del ac_view_2
pytest.gc_collect()
pytest.gc_collect()
assert capture == """
assert (
capture
== """
~ArrayClass()
"""
)
@pytest.unsupported_on_pypy
def test_cast_numpy_int64_to_uint64():
m.function_taking_uint64(123)
m.function_taking_uint64(np.uint64(123))
@@ -271,89 +310,94 @@ def test_constructors():
def test_overload_resolution(msg):
# Exact overload matches:
assert m.overloaded(np.array([1], dtype='float64')) == 'double'
assert m.overloaded(np.array([1], dtype='float32')) == 'float'
assert m.overloaded(np.array([1], dtype='ushort')) == 'unsigned short'
assert m.overloaded(np.array([1], dtype='intc')) == 'int'
assert m.overloaded(np.array([1], dtype='longlong')) == 'long long'
assert m.overloaded(np.array([1], dtype='complex')) == 'double complex'
assert m.overloaded(np.array([1], dtype='csingle')) == 'float complex'
assert m.overloaded(np.array([1], dtype="float64")) == "double"
assert m.overloaded(np.array([1], dtype="float32")) == "float"
assert m.overloaded(np.array([1], dtype="ushort")) == "unsigned short"
assert m.overloaded(np.array([1], dtype="intc")) == "int"
assert m.overloaded(np.array([1], dtype="longlong")) == "long long"
assert m.overloaded(np.array([1], dtype="complex")) == "double complex"
assert m.overloaded(np.array([1], dtype="csingle")) == "float complex"
# No exact match, should call first convertible version:
assert m.overloaded(np.array([1], dtype='uint8')) == 'double'
assert m.overloaded(np.array([1], dtype="uint8")) == "double"
with pytest.raises(TypeError) as excinfo:
m.overloaded("not an array")
assert msg(excinfo.value) == """
assert (
msg(excinfo.value)
== """
overloaded(): incompatible function arguments. The following argument types are supported:
1. (arg0: numpy.ndarray[float64]) -> str
2. (arg0: numpy.ndarray[float32]) -> str
3. (arg0: numpy.ndarray[int32]) -> str
4. (arg0: numpy.ndarray[uint16]) -> str
5. (arg0: numpy.ndarray[int64]) -> str
6. (arg0: numpy.ndarray[complex128]) -> str
7. (arg0: numpy.ndarray[complex64]) -> str
1. (arg0: numpy.ndarray[numpy.float64]) -> str
2. (arg0: numpy.ndarray[numpy.float32]) -> str
3. (arg0: numpy.ndarray[numpy.int32]) -> str
4. (arg0: numpy.ndarray[numpy.uint16]) -> str
5. (arg0: numpy.ndarray[numpy.int64]) -> str
6. (arg0: numpy.ndarray[numpy.complex128]) -> str
7. (arg0: numpy.ndarray[numpy.complex64]) -> str
Invoked with: 'not an array'
"""
)
assert m.overloaded2(np.array([1], dtype='float64')) == 'double'
assert m.overloaded2(np.array([1], dtype='float32')) == 'float'
assert m.overloaded2(np.array([1], dtype='complex64')) == 'float complex'
assert m.overloaded2(np.array([1], dtype='complex128')) == 'double complex'
assert m.overloaded2(np.array([1], dtype='float32')) == 'float'
assert m.overloaded2(np.array([1], dtype="float64")) == "double"
assert m.overloaded2(np.array([1], dtype="float32")) == "float"
assert m.overloaded2(np.array([1], dtype="complex64")) == "float complex"
assert m.overloaded2(np.array([1], dtype="complex128")) == "double complex"
assert m.overloaded2(np.array([1], dtype="float32")) == "float"
assert m.overloaded3(np.array([1], dtype='float64')) == 'double'
assert m.overloaded3(np.array([1], dtype='intc')) == 'int'
assert m.overloaded3(np.array([1], dtype="float64")) == "double"
assert m.overloaded3(np.array([1], dtype="intc")) == "int"
expected_exc = """
overloaded3(): incompatible function arguments. The following argument types are supported:
1. (arg0: numpy.ndarray[int32]) -> str
2. (arg0: numpy.ndarray[float64]) -> str
1. (arg0: numpy.ndarray[numpy.int32]) -> str
2. (arg0: numpy.ndarray[numpy.float64]) -> str
Invoked with: """
with pytest.raises(TypeError) as excinfo:
m.overloaded3(np.array([1], dtype='uintc'))
assert msg(excinfo.value) == expected_exc + repr(np.array([1], dtype='uint32'))
m.overloaded3(np.array([1], dtype="uintc"))
assert msg(excinfo.value) == expected_exc + repr(np.array([1], dtype="uint32"))
with pytest.raises(TypeError) as excinfo:
m.overloaded3(np.array([1], dtype='float32'))
assert msg(excinfo.value) == expected_exc + repr(np.array([1.], dtype='float32'))
m.overloaded3(np.array([1], dtype="float32"))
assert msg(excinfo.value) == expected_exc + repr(np.array([1.0], dtype="float32"))
with pytest.raises(TypeError) as excinfo:
m.overloaded3(np.array([1], dtype='complex'))
assert msg(excinfo.value) == expected_exc + repr(np.array([1. + 0.j]))
m.overloaded3(np.array([1], dtype="complex"))
assert msg(excinfo.value) == expected_exc + repr(np.array([1.0 + 0.0j]))
# Exact matches:
assert m.overloaded4(np.array([1], dtype='double')) == 'double'
assert m.overloaded4(np.array([1], dtype='longlong')) == 'long long'
assert m.overloaded4(np.array([1], dtype="double")) == "double"
assert m.overloaded4(np.array([1], dtype="longlong")) == "long long"
# Non-exact matches requiring conversion. Since float to integer isn't a
# save conversion, it should go to the double overload, but short can go to
# either (and so should end up on the first-registered, the long long).
assert m.overloaded4(np.array([1], dtype='float32')) == 'double'
assert m.overloaded4(np.array([1], dtype='short')) == 'long long'
assert m.overloaded4(np.array([1], dtype="float32")) == "double"
assert m.overloaded4(np.array([1], dtype="short")) == "long long"
assert m.overloaded5(np.array([1], dtype='double')) == 'double'
assert m.overloaded5(np.array([1], dtype='uintc')) == 'unsigned int'
assert m.overloaded5(np.array([1], dtype='float32')) == 'unsigned int'
assert m.overloaded5(np.array([1], dtype="double")) == "double"
assert m.overloaded5(np.array([1], dtype="uintc")) == "unsigned int"
assert m.overloaded5(np.array([1], dtype="float32")) == "unsigned int"
def test_greedy_string_overload():
"""Tests fix for #685 - ndarray shouldn't go to std::string overload"""
assert m.issue685("abc") == "string"
assert m.issue685(np.array([97, 98, 99], dtype='b')) == "array"
assert m.issue685(np.array([97, 98, 99], dtype="b")) == "array"
assert m.issue685(123) == "other"
def test_array_unchecked_fixed_dims(msg):
z1 = np.array([[1, 2], [3, 4]], dtype='float64')
z1 = np.array([[1, 2], [3, 4]], dtype="float64")
m.proxy_add2(z1, 10)
assert np.all(z1 == [[11, 12], [13, 14]])
with pytest.raises(ValueError) as excinfo:
m.proxy_add2(np.array([1., 2, 3]), 5.0)
assert msg(excinfo.value) == "array has incorrect number of dimensions: 1; expected 2"
m.proxy_add2(np.array([1.0, 2, 3]), 5.0)
assert (
msg(excinfo.value) == "array has incorrect number of dimensions: 1; expected 2"
)
expect_c = np.ndarray(shape=(3, 3, 3), buffer=np.array(range(3, 30)), dtype='int')
expect_c = np.ndarray(shape=(3, 3, 3), buffer=np.array(range(3, 30)), dtype="int")
assert np.all(m.proxy_init3(3.0) == expect_c)
expect_f = np.transpose(expect_c)
assert np.all(m.proxy_init3F(3.0) == expect_f)
@@ -364,13 +408,16 @@ def test_array_unchecked_fixed_dims(msg):
assert m.proxy_auxiliaries2(z1) == [11, 11, True, 2, 8, 2, 2, 4, 32]
assert m.proxy_auxiliaries2(z1) == m.array_auxiliaries2(z1)
assert m.proxy_auxiliaries1_const_ref(z1[0, :])
assert m.proxy_auxiliaries2_const_ref(z1)
def test_array_unchecked_dyn_dims(msg):
z1 = np.array([[1, 2], [3, 4]], dtype='float64')
z1 = np.array([[1, 2], [3, 4]], dtype="float64")
m.proxy_add2_dyn(z1, 10)
assert np.all(z1 == [[11, 12], [13, 14]])
expect_c = np.ndarray(shape=(3, 3, 3), buffer=np.array(range(3, 30)), dtype='int')
expect_c = np.ndarray(shape=(3, 3, 3), buffer=np.array(range(3, 30)), dtype="int")
assert np.all(m.proxy_init3_dyn(3.0) == expect_c)
assert m.proxy_auxiliaries2_dyn(z1) == [11, 11, True, 2, 8, 2, 2, 4, 32]
@@ -380,15 +427,15 @@ def test_array_unchecked_dyn_dims(msg):
def test_array_failure():
with pytest.raises(ValueError) as excinfo:
m.array_fail_test()
assert str(excinfo.value) == 'cannot create a pybind11::array from a nullptr'
assert str(excinfo.value) == "cannot create a pybind11::array from a nullptr"
with pytest.raises(ValueError) as excinfo:
m.array_t_fail_test()
assert str(excinfo.value) == 'cannot create a pybind11::array_t from a nullptr'
assert str(excinfo.value) == "cannot create a pybind11::array_t from a nullptr"
with pytest.raises(ValueError) as excinfo:
m.array_fail_test_negative_size()
assert str(excinfo.value) == 'negative dimensions are not allowed'
assert str(excinfo.value) == "negative dimensions are not allowed"
def test_initializer_list():
@@ -399,46 +446,93 @@ def test_initializer_list():
def test_array_resize(msg):
a = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='float64')
a = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9], dtype="float64")
m.array_reshape2(a)
assert(a.size == 9)
assert(np.all(a == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]))
assert a.size == 9
assert np.all(a == [[1, 2, 3], [4, 5, 6], [7, 8, 9]])
# total size change should succced with refcheck off
m.array_resize3(a, 4, False)
assert(a.size == 64)
assert a.size == 64
# ... and fail with refcheck on
try:
m.array_resize3(a, 3, True)
except ValueError as e:
assert(str(e).startswith("cannot resize an array"))
assert str(e).startswith("cannot resize an array")
# transposed array doesn't own data
b = a.transpose()
try:
m.array_resize3(b, 3, False)
except ValueError as e:
assert(str(e).startswith("cannot resize this array: it does not own its data"))
assert str(e).startswith("cannot resize this array: it does not own its data")
# ... but reshape should be fine
m.array_reshape2(b)
assert(b.shape == (8, 8))
assert b.shape == (8, 8)
@pytest.unsupported_on_pypy
@pytest.mark.xfail("env.PYPY")
def test_array_create_and_resize(msg):
a = m.create_and_resize(2)
assert(a.size == 4)
assert(np.all(a == 42.))
assert a.size == 4
assert np.all(a == 42.0)
@pytest.unsupported_on_py2
def test_index_using_ellipsis():
a = m.index_using_ellipsis(np.zeros((5, 6, 7)))
assert a.shape == (6,)
@pytest.unsupported_on_pypy
@pytest.mark.parametrize("forcecast", [False, True])
@pytest.mark.parametrize("contiguity", [None, "C", "F"])
@pytest.mark.parametrize("noconvert", [False, True])
@pytest.mark.filterwarnings(
"ignore:Casting complex values to real discards the imaginary part:numpy.ComplexWarning"
)
def test_argument_conversions(forcecast, contiguity, noconvert):
function_name = "accept_double"
if contiguity == "C":
function_name += "_c_style"
elif contiguity == "F":
function_name += "_f_style"
if forcecast:
function_name += "_forcecast"
if noconvert:
function_name += "_noconvert"
function = getattr(m, function_name)
for dtype in [np.dtype("float32"), np.dtype("float64"), np.dtype("complex128")]:
for order in ["C", "F"]:
for shape in [(2, 2), (1, 3, 1, 1), (1, 1, 1), (0,)]:
if not noconvert:
# If noconvert is not passed, only complex128 needs to be truncated and
# "cannot be safely obtained". So without `forcecast`, the argument shouldn't
# be accepted.
should_raise = dtype.name == "complex128" and not forcecast
else:
# If noconvert is passed, only float64 and the matching order is accepted.
# If at most one dimension has a size greater than 1, the array is also
# trivially contiguous.
trivially_contiguous = sum(1 for d in shape if d > 1) <= 1
should_raise = dtype.name != "float64" or (
contiguity is not None
and contiguity != order
and not trivially_contiguous
)
array = np.zeros(shape, dtype=dtype, order=order)
if not should_raise:
function(array)
else:
with pytest.raises(
TypeError, match="incompatible function arguments"
):
function(array)
@pytest.mark.xfail("env.PYPY")
def test_dtype_refcount_leak():
from sys import getrefcount
dtype = np.dtype(np.float_)
a = np.array([1], dtype=dtype)
before = getrefcount(dtype)