mirror of
https://github.com/pybind/pybind11.git
synced 2024-11-15 09:54:48 +00:00
bc041de0db
* Fix buffer protocol implementation According to the buffer protocol, `ndim` is a _required_ field [1], and should always be set correctly. Additionally, `shape` should be set if flags includes `PyBUF_ND` or higher [2]. The current implementation only set those fields if flags was `PyBUF_STRIDES`. [1] https://docs.python.org/3/c-api/buffer.html#request-independent-fields [2] https://docs.python.org/3/c-api/buffer.html#shape-strides-suboffsets * Apply suggestions from review * Obey contiguity requests for buffer protocol If a contiguous buffer is requested, and the underlying buffer isn't, then that should raise. This matches NumPy behaviour if you do something like: ``` struct.unpack_from('5d', np.arange(20.0)[::4]) # Raises for contiguity ``` Also, if a buffer is contiguous, then it can masquerade as a less-complex buffer, either by dropping strides, or even pretending to be 1D. This matches NumPy behaviour if you do something like: ``` a = np.full((3, 5), 30.0) struct.unpack_from('15d', a) # --> Produces 1D tuple from 2D buffer. ``` * Handle review comments * Test buffer protocol against NumPy * Also check PyBUF_FORMAT results
402 lines
14 KiB
Python
402 lines
14 KiB
Python
from __future__ import annotations
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import ctypes
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import io
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import struct
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import pytest
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import env
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from pybind11_tests import ConstructorStats
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from pybind11_tests import buffers as m
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np = pytest.importorskip("numpy")
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if m.long_double_and_double_have_same_size:
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# Determined by the compiler used to build the pybind11 tests
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# (e.g. MSVC gets here, but MinGW might not).
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np_float128 = None
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np_complex256 = None
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else:
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# Determined by the compiler used to build numpy (e.g. MinGW).
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np_float128 = getattr(np, *["float128"] * 2)
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np_complex256 = getattr(np, *["complex256"] * 2)
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CPP_NAME_FORMAT_NP_DTYPE_TABLE = [
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("PyObject *", "O", object),
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("bool", "?", np.bool_),
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("std::int8_t", "b", np.int8),
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("std::uint8_t", "B", np.uint8),
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("std::int16_t", "h", np.int16),
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("std::uint16_t", "H", np.uint16),
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("std::int32_t", "i", np.int32),
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("std::uint32_t", "I", np.uint32),
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("std::int64_t", "q", np.int64),
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("std::uint64_t", "Q", np.uint64),
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("float", "f", np.float32),
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("double", "d", np.float64),
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("long double", "g", np_float128),
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("std::complex<float>", "Zf", np.complex64),
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("std::complex<double>", "Zd", np.complex128),
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("std::complex<long double>", "Zg", np_complex256),
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]
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CPP_NAME_FORMAT_TABLE = [
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(cpp_name, format)
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for cpp_name, format, np_dtype in CPP_NAME_FORMAT_NP_DTYPE_TABLE
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if np_dtype is not None
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]
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CPP_NAME_NP_DTYPE_TABLE = [
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(cpp_name, np_dtype) for cpp_name, _, np_dtype in CPP_NAME_FORMAT_NP_DTYPE_TABLE
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]
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@pytest.mark.parametrize(("cpp_name", "np_dtype"), CPP_NAME_NP_DTYPE_TABLE)
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def test_format_descriptor_format_buffer_info_equiv(cpp_name, np_dtype):
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if np_dtype is None:
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pytest.skip(
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f"cpp_name=`{cpp_name}`: `long double` and `double` have same size."
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)
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if isinstance(np_dtype, str):
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pytest.skip(f"np.{np_dtype} does not exist.")
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np_array = np.array([], dtype=np_dtype)
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for other_cpp_name, expected_format in CPP_NAME_FORMAT_TABLE:
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format, np_array_is_matching = m.format_descriptor_format_buffer_info_equiv(
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other_cpp_name, np_array
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)
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assert format == expected_format
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if other_cpp_name == cpp_name:
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assert np_array_is_matching
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else:
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assert not np_array_is_matching
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def test_from_python():
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with pytest.raises(RuntimeError) as excinfo:
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m.Matrix(np.array([1, 2, 3])) # trying to assign a 1D array
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assert str(excinfo.value) == "Incompatible buffer format!"
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m3 = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
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m4 = m.Matrix(m3)
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for i in range(m4.rows()):
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for j in range(m4.cols()):
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assert m3[i, j] == m4[i, j]
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if env.GRAALPY:
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pytest.skip("ConstructorStats is incompatible with GraalPy.")
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cstats = ConstructorStats.get(m.Matrix)
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assert cstats.alive() == 1
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del m3, m4
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assert cstats.alive() == 0
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assert cstats.values() == ["2x3 matrix"]
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assert cstats.copy_constructions == 0
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# assert cstats.move_constructions >= 0 # Don't invoke any
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assert cstats.copy_assignments == 0
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assert cstats.move_assignments == 0
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# https://foss.heptapod.net/pypy/pypy/-/issues/2444
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# TODO: fix on recent PyPy
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@pytest.mark.xfail(
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env.PYPY, reason="PyPy 7.3.7 doesn't clear this anymore", strict=False
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)
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def test_to_python():
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mat = m.Matrix(5, 4)
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assert memoryview(mat).shape == (5, 4)
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assert mat[2, 3] == 0
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mat[2, 3] = 4.0
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mat[3, 2] = 7.0
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assert mat[2, 3] == 4
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assert mat[3, 2] == 7
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assert struct.unpack_from("f", mat, (3 * 4 + 2) * 4) == (7,)
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assert struct.unpack_from("f", mat, (2 * 4 + 3) * 4) == (4,)
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mat2 = np.array(mat, copy=False)
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assert mat2.shape == (5, 4)
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assert abs(mat2).sum() == 11
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assert mat2[2, 3] == 4
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assert mat2[3, 2] == 7
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mat2[2, 3] = 5
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assert mat2[2, 3] == 5
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if env.GRAALPY:
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pytest.skip("ConstructorStats is incompatible with GraalPy.")
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cstats = ConstructorStats.get(m.Matrix)
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assert cstats.alive() == 1
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del mat
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pytest.gc_collect()
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assert cstats.alive() == 1
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del mat2 # holds a mat reference
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pytest.gc_collect()
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assert cstats.alive() == 0
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assert cstats.values() == ["5x4 matrix"]
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assert cstats.copy_constructions == 0
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# assert cstats.move_constructions >= 0 # Don't invoke any
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assert cstats.copy_assignments == 0
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assert cstats.move_assignments == 0
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def test_inherited_protocol():
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"""SquareMatrix is derived from Matrix and inherits the buffer protocol"""
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matrix = m.SquareMatrix(5)
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assert memoryview(matrix).shape == (5, 5)
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assert np.asarray(matrix).shape == (5, 5)
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def test_pointer_to_member_fn():
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for cls in [m.Buffer, m.ConstBuffer, m.DerivedBuffer]:
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buf = cls()
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buf.value = 0x12345678
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value = struct.unpack("i", bytearray(buf))[0]
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assert value == 0x12345678
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def test_readonly_buffer():
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buf = m.BufferReadOnly(0x64)
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view = memoryview(buf)
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assert view[0] == 0x64
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assert view.readonly
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with pytest.raises(TypeError):
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view[0] = 0
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def test_selective_readonly_buffer():
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buf = m.BufferReadOnlySelect()
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memoryview(buf)[0] = 0x64
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assert buf.value == 0x64
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io.BytesIO(b"A").readinto(buf)
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assert buf.value == ord(b"A")
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buf.readonly = True
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with pytest.raises(TypeError):
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memoryview(buf)[0] = 0
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with pytest.raises(TypeError):
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io.BytesIO(b"1").readinto(buf)
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def test_ctypes_array_1d():
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char1d = (ctypes.c_char * 10)()
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int1d = (ctypes.c_int * 15)()
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long1d = (ctypes.c_long * 7)()
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for carray in (char1d, int1d, long1d):
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info = m.get_buffer_info(carray)
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assert info.itemsize == ctypes.sizeof(carray._type_)
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assert info.size == len(carray)
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assert info.ndim == 1
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assert info.shape == [info.size]
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assert info.strides == [info.itemsize]
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assert not info.readonly
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def test_ctypes_array_2d():
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char2d = ((ctypes.c_char * 10) * 4)()
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int2d = ((ctypes.c_int * 15) * 3)()
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long2d = ((ctypes.c_long * 7) * 2)()
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for carray in (char2d, int2d, long2d):
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info = m.get_buffer_info(carray)
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assert info.itemsize == ctypes.sizeof(carray[0]._type_)
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assert info.size == len(carray) * len(carray[0])
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assert info.ndim == 2
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assert info.shape == [len(carray), len(carray[0])]
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assert info.strides == [info.itemsize * len(carray[0]), info.itemsize]
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assert not info.readonly
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def test_ctypes_from_buffer():
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test_pystr = b"0123456789"
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for pyarray in (test_pystr, bytearray(test_pystr)):
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pyinfo = m.get_buffer_info(pyarray)
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if pyinfo.readonly:
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cbytes = (ctypes.c_char * len(pyarray)).from_buffer_copy(pyarray)
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cinfo = m.get_buffer_info(cbytes)
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else:
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cbytes = (ctypes.c_char * len(pyarray)).from_buffer(pyarray)
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cinfo = m.get_buffer_info(cbytes)
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assert cinfo.size == pyinfo.size
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assert cinfo.ndim == pyinfo.ndim
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assert cinfo.shape == pyinfo.shape
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assert cinfo.strides == pyinfo.strides
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assert not cinfo.readonly
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def test_buffer_docstring():
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assert (
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m.get_buffer_info.__doc__.strip()
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== "get_buffer_info(arg0: Buffer) -> pybind11_tests.buffers.buffer_info"
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)
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def test_buffer_exception():
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with pytest.raises(BufferError, match="Error getting buffer") as excinfo:
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memoryview(m.BrokenMatrix(1, 1))
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assert isinstance(excinfo.value.__cause__, RuntimeError)
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assert "for context" in str(excinfo.value.__cause__)
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@pytest.mark.parametrize("type", ["pybind11", "numpy"])
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def test_c_contiguous_to_pybuffer(type):
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if type == "pybind11":
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mat = m.Matrix(5, 4)
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elif type == "numpy":
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mat = np.empty((5, 4), dtype=np.float32)
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else:
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raise ValueError(f"Unknown parametrization {type}")
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info = m.get_py_buffer(mat, m.PyBUF_SIMPLE)
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assert info.format is None
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assert info.itemsize == ctypes.sizeof(ctypes.c_float)
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assert info.len == 5 * 4 * info.itemsize
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assert info.ndim == 0 # See discussion on PR #5407.
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assert info.shape is None
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assert info.strides is None
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assert info.suboffsets is None
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assert not info.readonly
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info = m.get_py_buffer(mat, m.PyBUF_SIMPLE | m.PyBUF_FORMAT)
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assert info.format == "f"
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assert info.itemsize == ctypes.sizeof(ctypes.c_float)
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assert info.len == 5 * 4 * info.itemsize
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assert info.ndim == 0 # See discussion on PR #5407.
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assert info.shape is None
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assert info.strides is None
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assert info.suboffsets is None
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assert not info.readonly
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info = m.get_py_buffer(mat, m.PyBUF_ND)
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assert info.itemsize == ctypes.sizeof(ctypes.c_float)
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assert info.len == 5 * 4 * info.itemsize
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assert info.ndim == 2
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assert info.shape == [5, 4]
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assert info.strides is None
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assert info.suboffsets is None
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assert not info.readonly
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info = m.get_py_buffer(mat, m.PyBUF_STRIDES)
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assert info.itemsize == ctypes.sizeof(ctypes.c_float)
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assert info.len == 5 * 4 * info.itemsize
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assert info.ndim == 2
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assert info.shape == [5, 4]
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assert info.strides == [4 * info.itemsize, info.itemsize]
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assert info.suboffsets is None
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assert not info.readonly
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info = m.get_py_buffer(mat, m.PyBUF_INDIRECT)
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assert info.itemsize == ctypes.sizeof(ctypes.c_float)
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assert info.len == 5 * 4 * info.itemsize
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assert info.ndim == 2
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assert info.shape == [5, 4]
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assert info.strides == [4 * info.itemsize, info.itemsize]
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assert info.suboffsets is None # Should be filled in here, but we don't use it.
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assert not info.readonly
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@pytest.mark.parametrize("type", ["pybind11", "numpy"])
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def test_fortran_contiguous_to_pybuffer(type):
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if type == "pybind11":
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mat = m.FortranMatrix(5, 4)
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elif type == "numpy":
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mat = np.empty((5, 4), dtype=np.float32, order="F")
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else:
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raise ValueError(f"Unknown parametrization {type}")
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# A Fortran-shaped buffer can only be accessed at PyBUF_STRIDES level or higher.
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info = m.get_py_buffer(mat, m.PyBUF_STRIDES)
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assert info.itemsize == ctypes.sizeof(ctypes.c_float)
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assert info.len == 5 * 4 * info.itemsize
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assert info.ndim == 2
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assert info.shape == [5, 4]
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assert info.strides == [info.itemsize, 5 * info.itemsize]
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assert info.suboffsets is None
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assert not info.readonly
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info = m.get_py_buffer(mat, m.PyBUF_INDIRECT)
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assert info.itemsize == ctypes.sizeof(ctypes.c_float)
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assert info.len == 5 * 4 * info.itemsize
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assert info.ndim == 2
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assert info.shape == [5, 4]
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assert info.strides == [info.itemsize, 5 * info.itemsize]
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assert info.suboffsets is None # Should be filled in here, but we don't use it.
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assert not info.readonly
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@pytest.mark.parametrize("type", ["pybind11", "numpy"])
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def test_discontiguous_to_pybuffer(type):
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if type == "pybind11":
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mat = m.DiscontiguousMatrix(5, 4, 2, 3)
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elif type == "numpy":
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mat = np.empty((5 * 2, 4 * 3), dtype=np.float32)[::2, ::3]
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else:
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raise ValueError(f"Unknown parametrization {type}")
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info = m.get_py_buffer(mat, m.PyBUF_STRIDES)
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assert info.itemsize == ctypes.sizeof(ctypes.c_float)
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assert info.len == 5 * 4 * info.itemsize
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assert info.ndim == 2
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assert info.shape == [5, 4]
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assert info.strides == [2 * 4 * 3 * info.itemsize, 3 * info.itemsize]
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assert info.suboffsets is None
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assert not info.readonly
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@pytest.mark.parametrize("type", ["pybind11", "numpy"])
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def test_to_pybuffer_contiguity(type):
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def check_strides(mat):
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# The full block is memset to 0, so fill it with non-zero in real spots.
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expected = np.arange(1, 5 * 4 + 1).reshape((5, 4))
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for i in range(5):
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for j in range(4):
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mat[i, j] = expected[i, j]
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# If all strides are correct, the exposed buffer should match the input.
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np.testing.assert_array_equal(np.array(mat), expected)
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if type == "pybind11":
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cmat = m.Matrix(5, 4) # C contiguous.
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fmat = m.FortranMatrix(5, 4) # Fortran contiguous.
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dmat = m.DiscontiguousMatrix(5, 4, 2, 3) # Not contiguous.
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expected_exception = BufferError
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elif type == "numpy":
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cmat = np.empty((5, 4), dtype=np.float32) # C contiguous.
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fmat = np.empty((5, 4), dtype=np.float32, order="F") # Fortran contiguous.
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dmat = np.empty((5 * 2, 4 * 3), dtype=np.float32)[::2, ::3] # Not contiguous.
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# NumPy incorrectly raises ValueError; when the minimum NumPy requirement is
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# above the version that fixes https://github.com/numpy/numpy/issues/3634 then
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# BufferError can be used everywhere.
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expected_exception = (BufferError, ValueError)
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else:
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raise ValueError(f"Unknown parametrization {type}")
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check_strides(cmat)
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# Should work in C-contiguous mode, but not Fortran order.
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m.get_py_buffer(cmat, m.PyBUF_C_CONTIGUOUS)
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m.get_py_buffer(cmat, m.PyBUF_ANY_CONTIGUOUS)
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with pytest.raises(expected_exception):
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m.get_py_buffer(cmat, m.PyBUF_F_CONTIGUOUS)
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check_strides(fmat)
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# These flags imply C-contiguity, so won't work.
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with pytest.raises(expected_exception):
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m.get_py_buffer(fmat, m.PyBUF_SIMPLE)
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with pytest.raises(expected_exception):
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m.get_py_buffer(fmat, m.PyBUF_ND)
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# Should work in Fortran-contiguous mode, but not C order.
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with pytest.raises(expected_exception):
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m.get_py_buffer(fmat, m.PyBUF_C_CONTIGUOUS)
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m.get_py_buffer(fmat, m.PyBUF_ANY_CONTIGUOUS)
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m.get_py_buffer(fmat, m.PyBUF_F_CONTIGUOUS)
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check_strides(dmat)
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# Should never work.
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with pytest.raises(expected_exception):
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m.get_py_buffer(dmat, m.PyBUF_SIMPLE)
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with pytest.raises(expected_exception):
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m.get_py_buffer(dmat, m.PyBUF_ND)
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with pytest.raises(expected_exception):
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m.get_py_buffer(dmat, m.PyBUF_C_CONTIGUOUS)
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with pytest.raises(expected_exception):
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m.get_py_buffer(dmat, m.PyBUF_ANY_CONTIGUOUS)
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with pytest.raises(expected_exception):
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m.get_py_buffer(dmat, m.PyBUF_F_CONTIGUOUS)
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