401 lines
14 KiB
Python
401 lines
14 KiB
Python
import numpy as np
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from numba.np.ufunc.ufuncbuilder import GUFuncBuilder
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from numba import vectorize, guvectorize
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from numba.np.ufunc import PyUFunc_One
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from numba.np.ufunc.dufunc import DUFunc as UFuncBuilder
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from numba.tests.support import tag, TestCase
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from numba.core import config
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import unittest
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class TestUfuncBuilding(TestCase):
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def test_basic_ufunc(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import add
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ufb = UFuncBuilder(add)
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cres = ufb.add("int32(int32, int32)")
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self.assertFalse(cres.objectmode)
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cres = ufb.add("int64(int64, int64)")
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self.assertFalse(cres.objectmode)
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ufunc = ufb.build_ufunc()
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def check(a):
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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self.assertEqual(b.dtype, a.dtype)
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a = np.arange(12, dtype='int32')
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check(a)
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# Non-contiguous dimension
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a = a[::2]
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check(a)
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a = a.reshape((2, 3))
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check(a)
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# Metadata
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self.assertEqual(ufunc.__name__, "add")
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self.assertIn("An addition", ufunc.__doc__)
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def test_ufunc_struct(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import add
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ufb = UFuncBuilder(add)
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cres = ufb.add("complex64(complex64, complex64)")
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self.assertFalse(cres.objectmode)
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ufunc = ufb.build_ufunc()
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def check(a):
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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self.assertEqual(b.dtype, a.dtype)
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a = np.arange(12, dtype='complex64') + 1j
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check(a)
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# Non-contiguous dimension
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a = a[::2]
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check(a)
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a = a.reshape((2, 3))
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check(a)
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def test_ufunc_forceobj(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import add
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ufb = UFuncBuilder(add, targetoptions={'forceobj': True})
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cres = ufb.add("int32(int32, int32)")
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self.assertTrue(cres.objectmode)
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ufunc = ufb.build_ufunc()
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a = np.arange(10, dtype='int32')
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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def test_nested_call(self):
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"""
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Check nested call to an implicitly-typed ufunc.
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"""
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from numba.tests.npyufunc.ufuncbuilding_usecases import outer
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builder = UFuncBuilder(outer,
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targetoptions={'nopython': True})
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builder.add("(int64, int64)")
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ufunc = builder.build_ufunc()
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self.assertEqual(ufunc(-1, 3), 2)
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def test_nested_call_explicit(self):
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"""
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Check nested call to an explicitly-typed ufunc.
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"""
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from numba.tests.npyufunc.ufuncbuilding_usecases import outer_explicit
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builder = UFuncBuilder(outer_explicit,
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targetoptions={'nopython': True})
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builder.add("(int64, int64)")
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ufunc = builder.build_ufunc()
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self.assertEqual(ufunc(-1, 3), 2)
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class TestUfuncBuildingJitDisabled(TestUfuncBuilding):
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def setUp(self):
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self.old_disable_jit = config.DISABLE_JIT
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config.DISABLE_JIT = False
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def tearDown(self):
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config.DISABLE_JIT = self.old_disable_jit
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class TestGUfuncBuilding(TestCase):
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def test_basic_gufunc(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import guadd
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gufb = GUFuncBuilder(guadd, "(x, y),(x, y)->(x, y)")
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cres = gufb.add("void(int32[:,:], int32[:,:], int32[:,:])")
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self.assertFalse(cres.objectmode)
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ufunc = gufb.build_ufunc()
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a = np.arange(10, dtype="int32").reshape(2, 5)
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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self.assertEqual(b.dtype, np.dtype('int32'))
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# Metadata
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self.assertEqual(ufunc.__name__, "guadd")
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self.assertIn("A generalized addition", ufunc.__doc__)
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def test_gufunc_struct(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import guadd
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gufb = GUFuncBuilder(guadd, "(x, y),(x, y)->(x, y)")
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cres = gufb.add("void(complex64[:,:], complex64[:,:], complex64[:,:])")
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self.assertFalse(cres.objectmode)
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ufunc = gufb.build_ufunc()
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a = np.arange(10, dtype="complex64").reshape(2, 5) + 1j
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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def test_gufunc_struct_forceobj(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import guadd
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gufb = GUFuncBuilder(guadd, "(x, y),(x, y)->(x, y)",
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targetoptions=dict(forceobj=True))
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cres = gufb.add("void(complex64[:,:], complex64[:,:], complex64[:,"
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":])")
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self.assertTrue(cres.objectmode)
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ufunc = gufb.build_ufunc()
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a = np.arange(10, dtype="complex64").reshape(2, 5) + 1j
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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class TestGUfuncBuildingJitDisabled(TestGUfuncBuilding):
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def setUp(self):
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self.old_disable_jit = config.DISABLE_JIT
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config.DISABLE_JIT = False
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def tearDown(self):
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config.DISABLE_JIT = self.old_disable_jit
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class TestVectorizeDecor(TestCase):
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_supported_identities = [0, 1, None, "reorderable"]
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def test_vectorize(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import add
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ufunc = vectorize(['int32(int32, int32)'])(add)
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a = np.arange(10, dtype='int32')
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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def test_vectorize_objmode(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import add
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ufunc = vectorize(['int32(int32, int32)'], forceobj=True)(add)
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a = np.arange(10, dtype='int32')
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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def test_vectorize_bool_return(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import equals
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ufunc = vectorize(['bool_(int32, int32)'])(equals)
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a = np.arange(10, dtype='int32')
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r = ufunc(a,a)
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self.assertPreciseEqual(r, np.ones(r.shape, dtype=np.bool_))
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def test_vectorize_identity(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import add
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sig = 'int32(int32, int32)'
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for identity in self._supported_identities:
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ufunc = vectorize([sig], identity=identity)(add)
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expected = None if identity == 'reorderable' else identity
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self.assertEqual(ufunc.identity, expected)
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# Default value is None
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ufunc = vectorize([sig])(add)
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self.assertIs(ufunc.identity, None)
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# Invalid values
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with self.assertRaises(ValueError):
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vectorize([sig], identity='none')(add)
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with self.assertRaises(ValueError):
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vectorize([sig], identity=2)(add)
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def test_vectorize_no_args(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import add
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a = np.linspace(0,1,10)
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b = np.linspace(1,2,10)
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ufunc = vectorize(add)
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self.assertPreciseEqual(ufunc(a,b), a + b)
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ufunc2 = vectorize(add)
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c = np.empty(10)
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ufunc2(a, b, c)
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self.assertPreciseEqual(c, a + b)
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def test_vectorize_only_kws(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import mul
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a = np.linspace(0,1,10)
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b = np.linspace(1,2,10)
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ufunc = vectorize(identity=PyUFunc_One, nopython=True)(mul)
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self.assertPreciseEqual(ufunc(a,b), a * b)
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def test_vectorize_output_kwarg(self):
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"""
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Passing the output array as a keyword argument (issue #1867).
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"""
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def check(ufunc):
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a = np.arange(10, 16, dtype='int32')
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out = np.zeros_like(a)
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got = ufunc(a, a, out=out)
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self.assertIs(got, out)
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self.assertPreciseEqual(out, a + a)
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with self.assertRaises(TypeError):
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ufunc(a, a, zzz=out)
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# With explicit sigs
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from numba.tests.npyufunc.ufuncbuilding_usecases import add
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ufunc = vectorize(['int32(int32, int32)'], nopython=True)(add)
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check(ufunc)
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# With implicit sig
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ufunc = vectorize(nopython=True)(add)
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check(ufunc) # compiling
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check(ufunc) # after compiling
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def test_guvectorize(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import guadd
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ufunc = guvectorize(['(int32[:,:], int32[:,:], int32[:,:])'],
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"(x,y),(x,y)->(x,y)")(guadd)
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a = np.arange(10, dtype='int32').reshape(2, 5)
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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def test_guvectorize_no_output(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import guadd
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ufunc = guvectorize(['(int32[:,:], int32[:,:], int32[:,:])'],
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"(x,y),(x,y),(x,y)")(guadd)
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a = np.arange(10, dtype='int32').reshape(2, 5)
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out = np.zeros_like(a)
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ufunc(a, a, out)
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self.assertPreciseEqual(a + a, out)
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def test_guvectorize_objectmode(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import guadd_obj
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ufunc = guvectorize(['(int32[:,:], int32[:,:], int32[:,:])'],
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"(x,y),(x,y)->(x,y)", forceobj=True)(guadd_obj)
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a = np.arange(10, dtype='int32').reshape(2, 5)
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b = ufunc(a, a)
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self.assertPreciseEqual(a + a, b)
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def test_guvectorize_scalar_objectmode(self):
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"""
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Test passing of scalars to object mode gufuncs.
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"""
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from numba.tests.npyufunc.ufuncbuilding_usecases import guadd_scalar_obj
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ufunc = guvectorize(['(int32[:,:], int32, int32[:,:])'],
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"(x,y),()->(x,y)", forceobj=True)(guadd_scalar_obj)
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a = np.arange(10, dtype='int32').reshape(2, 5)
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b = ufunc(a, 3)
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self.assertPreciseEqual(a + 3, b)
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def test_guvectorize_error_in_objectmode(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import guerror, \
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MyException
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ufunc = guvectorize(['(int32[:,:], int32[:,:], int32[:,:])'],
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"(x,y),(x,y)->(x,y)", forceobj=True)(guerror)
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a = np.arange(10, dtype='int32').reshape(2, 5)
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with self.assertRaises(MyException):
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ufunc(a, a)
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def test_guvectorize_identity(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import add, guadd
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args = (['(int32[:,:], int32[:,:], int32[:,:])'], "(x,y),(x,y)->(x,y)")
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for identity in self._supported_identities:
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ufunc = guvectorize(*args, identity=identity)(guadd)
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expected = None if identity == 'reorderable' else identity
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self.assertEqual(ufunc.identity, expected)
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# Default value is None
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ufunc = guvectorize(*args)(guadd)
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self.assertIs(ufunc.identity, None)
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# Invalid values
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with self.assertRaises(ValueError):
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guvectorize(*args, identity='none')(add)
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with self.assertRaises(ValueError):
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guvectorize(*args, identity=2)(add)
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def test_guvectorize_invalid_layout(self):
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from numba.tests.npyufunc.ufuncbuilding_usecases import guadd
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sigs = ['(int32[:,:], int32[:,:], int32[:,:])']
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# Syntax error
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with self.assertRaises(ValueError) as raises:
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guvectorize(sigs, ")-:")(guadd)
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self.assertIn("bad token in signature", str(raises.exception))
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# Output shape can't be inferred from inputs
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with self.assertRaises(NameError) as raises:
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guvectorize(sigs, "(x,y),(x,y)->(x,z,v)")(guadd)
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self.assertEqual(str(raises.exception),
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"undefined output symbols: v,z")
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# Arrow but no outputs
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with self.assertRaises(ValueError) as raises:
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guvectorize(sigs, "(x,y),(x,y),(x,y)->")(guadd)
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# (error message depends on Numpy version)
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class TestNEP13WithoutSignature(TestCase):
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def test_all(self):
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# note: no signatures specified
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@vectorize(nopython=True)
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def new_ufunc(hundreds, tens, ones):
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return 100*hundreds + 10*tens + ones
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# https://numpy.org/neps/nep-0013-ufunc-overrides.html
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class NEP13Array:
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def __init__(self, array):
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self.array = array
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def __array__(self):
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return self.array
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def tolist(self):
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return self.array.tolist()
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def __array_ufunc__(self, ufunc, method, *args, **kwargs):
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if method != "__call__":
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return NotImplemented
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return NEP13Array(ufunc(*[np.asarray(x) for x in args], **kwargs))
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# give it integers
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a = np.array([1, 2, 3], dtype=np.int64)
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b = np.array([4, 5, 6], dtype=np.int64)
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c = np.array([7, 8, 9], dtype=np.int64)
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all_np = new_ufunc(a, b, c)
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self.assertIsInstance(all_np, np.ndarray)
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self.assertEqual(all_np.tolist(), [147, 258, 369])
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nep13_1 = new_ufunc(NEP13Array(a), b, c)
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self.assertIsInstance(nep13_1, NEP13Array)
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self.assertEqual(nep13_1.tolist(), [147, 258, 369])
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nep13_2 = new_ufunc(a, NEP13Array(b), c)
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self.assertIsInstance(nep13_2, NEP13Array)
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self.assertEqual(nep13_2.tolist(), [147, 258, 369])
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nep13_3 = new_ufunc(a, b, NEP13Array(c))
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self.assertIsInstance(nep13_3, NEP13Array)
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self.assertEqual(nep13_3.tolist(), [147, 258, 369])
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# give it floats
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a = np.array([1.1, 2.2, 3.3], dtype=np.float64)
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b = np.array([4.4, 5.5, 6.6], dtype=np.float64)
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c = np.array([7.7, 8.8, 9.9], dtype=np.float64)
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all_np = new_ufunc(a, b, c)
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self.assertIsInstance(all_np, np.ndarray)
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self.assertEqual(all_np.tolist(), [161.7, 283.8, 405.9])
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nep13_1 = new_ufunc(NEP13Array(a), b, c)
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self.assertIsInstance(nep13_1, NEP13Array)
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self.assertEqual(nep13_1.tolist(), [161.7, 283.8, 405.9])
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nep13_2 = new_ufunc(a, NEP13Array(b), c)
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self.assertIsInstance(nep13_2, NEP13Array)
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self.assertEqual(nep13_2.tolist(), [161.7, 283.8, 405.9])
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nep13_3 = new_ufunc(a, b, NEP13Array(c))
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self.assertIsInstance(nep13_3, NEP13Array)
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self.assertEqual(nep13_3.tolist(), [161.7, 283.8, 405.9])
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class TestVectorizeDecorJitDisabled(TestVectorizeDecor):
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def setUp(self):
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self.old_disable_jit = config.DISABLE_JIT
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config.DISABLE_JIT = False
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def tearDown(self):
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config.DISABLE_JIT = self.old_disable_jit
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if __name__ == '__main__':
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unittest.main()
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