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python-numba
numpy21.patch
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File numpy21.patch of Package python-numba
From 5f2a3d60fc9c1e25bec9fd6de0b0b8bae6f142da Mon Sep 17 00:00:00 2001 From: kc611 <ckaustubhm06@gmail.com> Date: Mon, 30 Sep 2024 23:08:18 +0530 Subject: [PATCH 01/22] Added NumPy 2.1 Support --- numba/cpython/randomimpl.py | 6 ++- numba/cuda/tests/cudapy/test_debug.py | 2 +- numba/np/arrayobj.py | 6 +-- numba/np/math/numbers.py | 5 +++ numba/np/npyfuncs.py | 58 +++++++++++++++++---------- numba/np/old_arraymath.py | 2 + numba/np/random/old_distributions.py | 4 +- numba/np/ufunc_db.py | 36 +++++++++++++++++ numba/tests/test_array_methods.py | 19 ++++++--- 9 files changed, 105 insertions(+), 33 deletions(-) Index: numba-0.60.0/numba/cpython/randomimpl.py =================================================================== --- numba-0.60.0.orig/numba/cpython/randomimpl.py +++ numba-0.60.0/numba/cpython/randomimpl.py @@ -17,7 +17,7 @@ from numba.core.imputils import (Registr from numba.core.typing import signature from numba.core import types, cgutils from numba.core.errors import NumbaTypeError - +from numba.np.random._constants import LONG_MAX registry = Registry('randomimpl') lower = registry.lower @@ -1798,6 +1798,10 @@ def zipf_impl(a): U = 1.0 - np.random.random() V = np.random.random() X = int(math.floor(U ** (-1.0 / am1))) + + if (X > LONG_MAX or X < 1.0): + continue + T = (1.0 + 1.0 / X) ** am1 if X >= 1 and V * X * (T - 1.0) / (b - 1.0) <= (T / b): return X Index: numba-0.60.0/numba/np/arrayobj.py =================================================================== --- numba-0.60.0.orig/numba/np/arrayobj.py +++ numba-0.60.0/numba/np/arrayobj.py @@ -1932,17 +1932,23 @@ def numpy_geomspace(start, stop, num=50) raise ValueError('Geometric sequence cannot include zero') start = result_dtype(start) stop = result_dtype(stop) - both_imaginary = (start.real == 0) & (stop.real == 0) - both_negative = (np.sign(start) == -1) & (np.sign(stop) == -1) - out_sign = 1 - if both_imaginary: - start = start.imag - stop = stop.imag - out_sign = 1j - if both_negative: - start = -start - stop = -stop - out_sign = -out_sign + if numpy_version < (2, 0): + both_imaginary = (start.real == 0) & (stop.real == 0) + both_negative = (np.sign(start) == -1) & (np.sign(stop) == -1) + out_sign = 1 + if both_imaginary: + start = start.imag + stop = stop.imag + out_sign = 1j + if both_negative: + start = -start + stop = -stop + out_sign = -out_sign + else: + out_sign = np.sign(start) + start /= out_sign + stop /= out_sign + logstart = np.log10(start) logstop = np.log10(stop) result = np.logspace(logstart, logstop, num) @@ -2144,11 +2150,18 @@ def array_reshape_vararg(context, builde return array_reshape(context, builder, new_sig, new_args) -@overload(np.reshape) -def np_reshape(a, newshape): - def np_reshape_impl(a, newshape): - return a.reshape(newshape) - return np_reshape_impl +if numpy_version < (2, 1): + @overload(np.reshape) + def np_reshape(a, newshape): + def np_reshape_impl(a, newshape): + return a.reshape(newshape) + return np_reshape_impl +else: + @overload(np.reshape) + def np_reshape(a, shape): + def np_reshape_impl(a, shape): + return a.reshape(shape) + return np_reshape_impl @overload(np.resize) Index: numba-0.60.0/numba/np/math/numbers.py =================================================================== --- numba-0.60.0.orig/numba/np/math/numbers.py +++ numba-0.60.0/numba/np/math/numbers.py @@ -397,6 +397,11 @@ def int_abs_impl(context, builder, sig, return impl_ret_untracked(context, builder, sig.return_type, res) +def identity_impl(context, builder, sig, args): + [x] = args + return impl_ret_untracked(context, builder, sig.return_type, x) + + def uint_abs_impl(context, builder, sig, args): [x] = args return impl_ret_untracked(context, builder, sig.return_type, x) Index: numba-0.60.0/numba/np/npyfuncs.py =================================================================== --- numba-0.60.0.orig/numba/np/npyfuncs.py +++ numba-0.60.0/numba/np/npyfuncs.py @@ -16,6 +16,7 @@ from numba.core import typing, types, er from numba.core.extending import register_jitable from numba.np import npdatetime from numba.np.math import cmathimpl, mathimpl, numbers +from numba.np.numpy_support import numpy_version # some NumPy constants. Note that we could generate some of them using # the math library, but having the values copied from npy_math seems to @@ -580,29 +581,42 @@ def np_complex_sign_impl(context, builde # equivalent to complex sign in NumPy's sign # but implemented via selects, balancing the 4 cases. _check_arity_and_homogeneity(sig, args, 1) - op = args[0] - ty = sig.args[0] - float_ty = ty.underlying_float - ZERO = context.get_constant(float_ty, 0.0) - ONE = context.get_constant(float_ty, 1.0) - MINUS_ONE = context.get_constant(float_ty, -1.0) - NAN = context.get_constant(float_ty, float('nan')) - result = context.make_complex(builder, ty) - result.real = ZERO - result.imag = ZERO - - cmp_sig = typing.signature(types.boolean, *[ty] * 2) - cmp_args = [op, result._getvalue()] - arg1_ge_arg2 = np_complex_ge_impl(context, builder, cmp_sig, cmp_args) - arg1_eq_arg2 = np_complex_eq_impl(context, builder, cmp_sig, cmp_args) - arg1_lt_arg2 = np_complex_lt_impl(context, builder, cmp_sig, cmp_args) - - real_when_ge = builder.select(arg1_eq_arg2, ZERO, ONE) - real_when_nge = builder.select(arg1_lt_arg2, MINUS_ONE, NAN) - result.real = builder.select(arg1_ge_arg2, real_when_ge, real_when_nge) + if numpy_version >= (2, 0): + # NumPy >= 2.0.0 + def complex_sign(z): + abs = math.hypot(z.real, z.imag) + if abs == 0: + return 0 + 0j + else: + return z / abs + + res = context.compile_internal(builder, complex_sign, sig, args) + return impl_ret_untracked(context, builder, sig.return_type, res) + else: + op = args[0] + ty = sig.args[0] + result = context.make_complex(builder, ty) + float_ty = ty.underlying_float + + ZERO = context.get_constant(float_ty, 0.0) + ONE = context.get_constant(float_ty, 1.0) + MINUS_ONE = context.get_constant(float_ty, -1.0) + NAN = context.get_constant(float_ty, float('nan')) + + result.real = ZERO + result.imag = ZERO + cmp_sig = typing.signature(types.boolean, *[ty] * 2) + cmp_args = [op, result._getvalue()] + arg1_ge_arg2 = np_complex_ge_impl(context, builder, cmp_sig, cmp_args) + arg1_eq_arg2 = np_complex_eq_impl(context, builder, cmp_sig, cmp_args) + arg1_lt_arg2 = np_complex_lt_impl(context, builder, cmp_sig, cmp_args) + + real_when_ge = builder.select(arg1_eq_arg2, ZERO, ONE) + real_when_nge = builder.select(arg1_lt_arg2, MINUS_ONE, NAN) + result.real = builder.select(arg1_ge_arg2, real_when_ge, real_when_nge) - return result._getvalue() + return result._getvalue() ######################################################################## Index: numba-0.60.0/numba/np/ufunc_db.py =================================================================== --- numba-0.60.0.orig/numba/np/ufunc_db.py +++ numba-0.60.0/numba/np/ufunc_db.py @@ -583,16 +583,58 @@ def _fill_ufunc_db(ufunc_db): 'f->f': npyfuncs.np_real_floor_impl, 'd->d': npyfuncs.np_real_floor_impl, } + if numpy_version >= (2, 1): + ufunc_db[np.floor].update({ + '?->?': numbers.identity_impl, + 'b->b': numbers.identity_impl, + 'B->B': numbers.identity_impl, + 'h->h': numbers.identity_impl, + 'H->H': numbers.identity_impl, + 'i->i': numbers.identity_impl, + 'I->I': numbers.identity_impl, + 'l->l': numbers.identity_impl, + 'L->L': numbers.identity_impl, + 'q->q': numbers.identity_impl, + 'Q->Q': numbers.identity_impl, + }) ufunc_db[np.ceil] = { 'f->f': npyfuncs.np_real_ceil_impl, 'd->d': npyfuncs.np_real_ceil_impl, } + if numpy_version >= (2, 1): + ufunc_db[np.ceil].update({ + '?->?': numbers.identity_impl, + 'b->b': numbers.identity_impl, + 'B->B': numbers.identity_impl, + 'h->h': numbers.identity_impl, + 'H->H': numbers.identity_impl, + 'i->i': numbers.identity_impl, + 'I->I': numbers.identity_impl, + 'l->l': numbers.identity_impl, + 'L->L': numbers.identity_impl, + 'q->q': numbers.identity_impl, + 'Q->Q': numbers.identity_impl, + }) ufunc_db[np.trunc] = { 'f->f': npyfuncs.np_real_trunc_impl, 'd->d': npyfuncs.np_real_trunc_impl, } + if numpy_version >= (2, 1): + ufunc_db[np.trunc].update({ + '?->?': numbers.identity_impl, + 'b->b': numbers.identity_impl, + 'B->B': numbers.identity_impl, + 'h->h': numbers.identity_impl, + 'H->H': numbers.identity_impl, + 'i->i': numbers.identity_impl, + 'I->I': numbers.identity_impl, + 'l->l': numbers.identity_impl, + 'L->L': numbers.identity_impl, + 'q->q': numbers.identity_impl, + 'Q->Q': numbers.identity_impl, + }) ufunc_db[np.fabs] = { 'f->f': npyfuncs.np_real_fabs_impl, Index: numba-0.60.0/numba/tests/test_array_methods.py =================================================================== --- numba-0.60.0.orig/numba/tests/test_array_methods.py +++ numba-0.60.0/numba/tests/test_array_methods.py @@ -774,13 +774,20 @@ class TestArrayMethods(MemoryLeakMixin, check_arr(arr.reshape((2, 3, 4))) check_arr(arr.reshape((2, 3, 4)).T) check_arr(arr.reshape((2, 3, 4))[::2]) - for v in (0.0, 1.5, float('nan')): - arr = np.array([v]).reshape(()) - check_arr(arr) arr = np.array(["Hello", "", "world"]) check_arr(arr) + for v in (0.0, 1.5, float('nan')): + arr = np.array([v]).reshape(()) + if numpy_version < (2, 1): + check_arr(arr) + else: + with self.assertRaises(ValueError) as raises: + njit((typeof(arr),))(pyfunc) + self.assertEqual(str(raises.exception), + "Calling nonzero on 0d arrays is not allowed. Use np.atleast_1d(scalar).nonzero() instead.") + def test_array_nonzero(self): self.check_nonzero(array_nonzero) Index: numba-0.60.0/docs/upcoming_changes/9741.highlight.rst =================================================================== --- /dev/null +++ numba-0.60.0/docs/upcoming_changes/9741.highlight.rst @@ -0,0 +1,4 @@ +Added Support for NumPy 2.1 +--------------------------- + +This release adds support for NumPy 2.1 (excluding the NEP-050 semantics). Index: numba-0.60.0/numba/tests/test_ufuncs.py =================================================================== --- numba-0.60.0.orig/numba/tests/test_ufuncs.py +++ numba-0.60.0/numba/tests/test_ufuncs.py @@ -18,7 +18,6 @@ from numba.np import numpy_support from numba.core.registry import cpu_target from numba.core.base import BaseContext from numba.np import ufunc_db -from numba.tests.support import expected_failure_np2 is32bits = tuple.__itemsize__ == 4 iswindows = sys.platform.startswith('win32') @@ -1696,8 +1695,6 @@ class TestLoopTypesComplex(_LoopTypesTes TestLoopTypesComplex.autogenerate() -expected_failure_np2(TestLoopTypesComplex.test_sign_F_F) -expected_failure_np2(TestLoopTypesComplex.test_sign_D_D) class TestLoopTypesDatetime(_LoopTypesTester): Index: numba-0.60.0/numba/core/typing/arraydecl.py =================================================================== --- numba-0.60.0.orig/numba/core/typing/arraydecl.py +++ numba-0.60.0/numba/core/typing/arraydecl.py @@ -415,6 +415,11 @@ class ArrayAttribute(AttributeTemplate): def resolve_nonzero(self, ary, args, kws): assert not args assert not kws + if ary.ndim == 0 and numpy_version >= (2, 1): + raise ValueError( + "Calling nonzero on 0d arrays is not allowed." + " Use np.atleast_1d(scalar).nonzero() instead." + ) # 0-dim arrays return one result array ndim = max(ary.ndim, 1) retty = types.UniTuple(types.Array(types.intp, 1, 'C'), ndim) Index: numba-0.60.0/numba/np/random/_constants.py =================================================================== --- numba-0.60.0.orig/numba/np/random/_constants.py +++ numba-0.60.0/numba/np/random/_constants.py @@ -1,4 +1,5 @@ import numpy as np +import ctypes # These constants are directly obtained from: # https://github.com/numpy/numpy/blob/caccd283941b0bade7b71056138ded5379b1625f/numpy/random/src/distributions/ziggurat_constants.h @@ -1222,6 +1223,7 @@ UINT8_MAX = 255 UINT16_MAX = 65535 UINT32_MAX = 4294967295 UINT64_MAX = 18446744073709551615 +LONG_MAX = (1 << ( 8 * ctypes.sizeof(ctypes.c_long) - 1)) - 1 LS2PI = 0.91893853320467267 TWELFTH = 0.083333333333333333333333 Index: numba-0.60.0/numba/__init__.py =================================================================== --- numba-0.60.0.orig/numba/__init__.py +++ numba-0.60.0/numba/__init__.py @@ -34,13 +34,13 @@ def _ensure_critical_deps(): import numpy as np numpy_version = extract_version(np) - if numpy_version < (1, 22): - msg = (f"Numba needs NumPy 1.22 or greater. Got NumPy " + if numpy_version < (1, 24): + msg = (f"Numba needs NumPy 1.24 or greater. Got NumPy " f"{numpy_version[0]}.{numpy_version[1]}.") raise ImportError(msg) - if numpy_version > (2, 0): - msg = (f"Numba needs NumPy 2.0 or less. Got NumPy " + if numpy_version > (2, 1): + msg = (f"Numba needs NumPy 2.1 or less. Got NumPy " f"{numpy_version[0]}.{numpy_version[1]}.") raise ImportError(msg) Index: numba-0.60.0/numba/np/random/distributions.py =================================================================== --- a/numba/np/random/distributions.py +++ b/numba/np/random/distributions.py @@ -394,8 +394,10 @@ def random_geometric(bitgen, p): def random_zipf(bitgen, a): am1 = a - 1.0 b = pow(2.0, am1) + Umin = pow(INT64_MAX, -am1) while 1: - U = 1.0 - next_double(bitgen) + U01 = next_double(bitgen) + U = U01*Umin + (1 - U01) V = next_double(bitgen) X = np.floor(pow(U, -1.0 / am1)) if (X > INT64_MAX or X < 1.0):
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