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