mirror of
https://github.com/pybind/pybind11.git
synced 2024-11-11 08:03:55 +00:00
ae5a8f7eb3
The only part of the vectorize code that actually needs c-contiguous is the "trivial" broadcast; for non-trivial arguments, the code already uses strides properly (and so handles C-style, F-style, neither, slices, etc.) This commit rewrites `broadcast` to additionally check for C-contiguous storage, then takes off the `c_style` flag for the arguments, which will keep the functionality more or less the same, except for no longer requiring an array copy for non-c-contiguous input arrays. Additionally, if we're given a singleton slice (e.g. a[0::4, 0::4] for a 4x4 or smaller array), we no longer fail triviality because the trivial code path never actually uses the strides on a singleton.
134 lines
5.5 KiB
Python
134 lines
5.5 KiB
Python
import pytest
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pytestmark = pytest.requires_numpy
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with pytest.suppress(ImportError):
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import numpy as np
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def test_vectorize(capture):
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from pybind11_tests import vectorized_func, vectorized_func2, vectorized_func3
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assert np.isclose(vectorized_func3(np.array(3 + 7j)), [6 + 14j])
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for f in [vectorized_func, vectorized_func2]:
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with capture:
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assert np.isclose(f(1, 2, 3), 6)
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assert capture == "my_func(x:int=1, y:float=2, z:float=3)"
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with capture:
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assert np.isclose(f(np.array(1), np.array(2), 3), 6)
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assert capture == "my_func(x:int=1, y:float=2, z:float=3)"
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with capture:
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assert np.allclose(f(np.array([1, 3]), np.array([2, 4]), 3), [6, 36])
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assert capture == """
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my_func(x:int=1, y:float=2, z:float=3)
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my_func(x:int=3, y:float=4, z:float=3)
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"""
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with capture:
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a, b, c = np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3
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assert np.allclose(f(a, b, c), a * b * c)
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assert capture == """
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my_func(x:int=1, y:float=2, z:float=3)
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my_func(x:int=3, y:float=4, z:float=3)
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my_func(x:int=5, y:float=6, z:float=3)
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my_func(x:int=7, y:float=8, z:float=3)
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my_func(x:int=9, y:float=10, z:float=3)
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my_func(x:int=11, y:float=12, z:float=3)
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"""
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with capture:
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a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2
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assert np.allclose(f(a, b, c), a * b * c)
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assert capture == """
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my_func(x:int=1, y:float=2, z:float=2)
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my_func(x:int=2, y:float=3, z:float=2)
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my_func(x:int=3, y:float=4, z:float=2)
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my_func(x:int=4, y:float=2, z:float=2)
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my_func(x:int=5, y:float=3, z:float=2)
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my_func(x:int=6, y:float=4, z:float=2)
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"""
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with capture:
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a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2
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assert np.allclose(f(a, b, c), a * b * c)
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assert capture == """
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my_func(x:int=1, y:float=2, z:float=2)
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my_func(x:int=2, y:float=2, z:float=2)
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my_func(x:int=3, y:float=2, z:float=2)
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my_func(x:int=4, y:float=3, z:float=2)
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my_func(x:int=5, y:float=3, z:float=2)
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my_func(x:int=6, y:float=3, z:float=2)
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"""
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with capture:
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a, b, c = np.array([[1, 2, 3], [4, 5, 6]], order='F'), np.array([[2], [3]]), 2
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assert np.allclose(f(a, b, c), a * b * c)
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assert capture == """
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my_func(x:int=1, y:float=2, z:float=2)
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my_func(x:int=2, y:float=2, z:float=2)
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my_func(x:int=3, y:float=2, z:float=2)
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my_func(x:int=4, y:float=3, z:float=2)
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my_func(x:int=5, y:float=3, z:float=2)
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my_func(x:int=6, y:float=3, z:float=2)
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"""
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with capture:
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a, b, c = np.array([[1, 2, 3], [4, 5, 6]])[::, ::2], np.array([[2], [3]]), 2
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assert np.allclose(f(a, b, c), a * b * c)
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assert capture == """
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my_func(x:int=1, y:float=2, z:float=2)
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my_func(x:int=3, y:float=2, z:float=2)
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my_func(x:int=4, y:float=3, z:float=2)
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my_func(x:int=6, y:float=3, z:float=2)
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"""
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with capture:
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a, b, c = np.array([[1, 2, 3], [4, 5, 6]], order='F')[::, ::2], np.array([[2], [3]]), 2
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assert np.allclose(f(a, b, c), a * b * c)
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assert capture == """
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my_func(x:int=1, y:float=2, z:float=2)
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my_func(x:int=3, y:float=2, z:float=2)
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my_func(x:int=4, y:float=3, z:float=2)
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my_func(x:int=6, y:float=3, z:float=2)
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"""
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def test_type_selection():
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from pybind11_tests import selective_func
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assert selective_func(np.array([1], dtype=np.int32)) == "Int branch taken."
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assert selective_func(np.array([1.0], dtype=np.float32)) == "Float branch taken."
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assert selective_func(np.array([1.0j], dtype=np.complex64)) == "Complex float branch taken."
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def test_docs(doc):
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from pybind11_tests import vectorized_func
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assert doc(vectorized_func) == """
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vectorized_func(arg0: numpy.ndarray[int32], arg1: numpy.ndarray[float32], arg2: numpy.ndarray[float64]) -> object
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""" # noqa: E501 line too long
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def test_trivial_broadcasting():
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from pybind11_tests import vectorized_is_trivial
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assert vectorized_is_trivial(1, 2, 3)
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assert vectorized_is_trivial(np.array(1), np.array(2), 3)
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assert vectorized_is_trivial(np.array([1, 3]), np.array([2, 4]), 3)
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assert vectorized_is_trivial(
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np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3)
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assert not vectorized_is_trivial(
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np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2)
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assert not vectorized_is_trivial(
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np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2)
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z1 = np.array([[1, 2, 3, 4], [5, 6, 7, 8]], dtype='int32')
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z2 = np.array(z1, dtype='float32')
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z3 = np.array(z1, dtype='float64')
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assert vectorized_is_trivial(z1, z2, z3)
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assert not vectorized_is_trivial(z1[::2, ::2], 1, 1)
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assert vectorized_is_trivial(1, 1, z1[::2, ::2])
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assert not vectorized_is_trivial(1, 1, z3[::2, ::2])
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assert vectorized_is_trivial(z1, 1, z3[1::4, 1::4])
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y1 = np.array(z1, order='F')
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y2 = np.array(y1)
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y3 = np.array(y1)
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assert not vectorized_is_trivial(y1, y2, y3)
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assert not vectorized_is_trivial(y1, z2, z3)
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assert not vectorized_is_trivial(y1, 1, 1)
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