Accepting request 1216757 from devel:languages:python:numeric
OBS-URL: https://build.opensuse.org/request/show/1216757 OBS-URL: https://build.opensuse.org/package/show/openSUSE:Factory/python-numba?expand=0&rev=49
This commit is contained in:
commit
3031b5febc
389
numpy21.patch
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389
numpy21.patch
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@ -0,0 +1,389 @@
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From 5f2a3d60fc9c1e25bec9fd6de0b0b8bae6f142da Mon Sep 17 00:00:00 2001
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From: kc611 <ckaustubhm06@gmail.com>
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Date: Mon, 30 Sep 2024 23:08:18 +0530
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Subject: [PATCH 01/22] Added NumPy 2.1 Support
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---
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numba/cpython/randomimpl.py | 6 ++-
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numba/cuda/tests/cudapy/test_debug.py | 2 +-
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numba/np/arrayobj.py | 6 +--
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numba/np/math/numbers.py | 5 +++
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numba/np/npyfuncs.py | 58 +++++++++++++++++----------
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numba/np/old_arraymath.py | 2 +
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numba/np/random/old_distributions.py | 4 +-
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numba/np/ufunc_db.py | 36 +++++++++++++++++
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numba/tests/test_array_methods.py | 19 ++++++---
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9 files changed, 105 insertions(+), 33 deletions(-)
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Index: numba-0.60.0/numba/cpython/randomimpl.py
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===================================================================
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--- numba-0.60.0.orig/numba/cpython/randomimpl.py
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+++ numba-0.60.0/numba/cpython/randomimpl.py
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@@ -17,7 +17,7 @@ from numba.core.imputils import (Registr
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from numba.core.typing import signature
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from numba.core import types, cgutils
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from numba.core.errors import NumbaTypeError
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-
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+from numba.np.random._constants import LONG_MAX
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registry = Registry('randomimpl')
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lower = registry.lower
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@@ -1798,6 +1798,10 @@ def zipf_impl(a):
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U = 1.0 - np.random.random()
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V = np.random.random()
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X = int(math.floor(U ** (-1.0 / am1)))
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+
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+ if (X > LONG_MAX or X < 1.0):
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+ continue
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+
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T = (1.0 + 1.0 / X) ** am1
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if X >= 1 and V * X * (T - 1.0) / (b - 1.0) <= (T / b):
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return X
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Index: numba-0.60.0/numba/np/arrayobj.py
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===================================================================
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--- numba-0.60.0.orig/numba/np/arrayobj.py
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+++ numba-0.60.0/numba/np/arrayobj.py
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@@ -1932,17 +1932,23 @@ def numpy_geomspace(start, stop, num=50)
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raise ValueError('Geometric sequence cannot include zero')
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start = result_dtype(start)
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stop = result_dtype(stop)
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- both_imaginary = (start.real == 0) & (stop.real == 0)
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- both_negative = (np.sign(start) == -1) & (np.sign(stop) == -1)
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- out_sign = 1
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- if both_imaginary:
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- start = start.imag
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- stop = stop.imag
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- out_sign = 1j
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- if both_negative:
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- start = -start
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- stop = -stop
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- out_sign = -out_sign
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+ if numpy_version < (2, 0):
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+ both_imaginary = (start.real == 0) & (stop.real == 0)
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+ both_negative = (np.sign(start) == -1) & (np.sign(stop) == -1)
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+ out_sign = 1
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+ if both_imaginary:
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+ start = start.imag
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+ stop = stop.imag
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+ out_sign = 1j
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+ if both_negative:
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+ start = -start
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+ stop = -stop
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+ out_sign = -out_sign
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+ else:
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+ out_sign = np.sign(start)
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+ start /= out_sign
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+ stop /= out_sign
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+
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logstart = np.log10(start)
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logstop = np.log10(stop)
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result = np.logspace(logstart, logstop, num)
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@@ -2144,11 +2150,18 @@ def array_reshape_vararg(context, builde
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return array_reshape(context, builder, new_sig, new_args)
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-@overload(np.reshape)
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-def np_reshape(a, newshape):
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- def np_reshape_impl(a, newshape):
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- return a.reshape(newshape)
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- return np_reshape_impl
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+if numpy_version < (2, 1):
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+ @overload(np.reshape)
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+ def np_reshape(a, newshape):
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+ def np_reshape_impl(a, newshape):
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+ return a.reshape(newshape)
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+ return np_reshape_impl
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+else:
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+ @overload(np.reshape)
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+ def np_reshape(a, shape):
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+ def np_reshape_impl(a, shape):
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+ return a.reshape(shape)
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+ return np_reshape_impl
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@overload(np.resize)
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Index: numba-0.60.0/numba/np/math/numbers.py
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===================================================================
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--- numba-0.60.0.orig/numba/np/math/numbers.py
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+++ numba-0.60.0/numba/np/math/numbers.py
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@@ -397,6 +397,11 @@ def int_abs_impl(context, builder, sig,
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return impl_ret_untracked(context, builder, sig.return_type, res)
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+def identity_impl(context, builder, sig, args):
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+ [x] = args
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+ return impl_ret_untracked(context, builder, sig.return_type, x)
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+
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+
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def uint_abs_impl(context, builder, sig, args):
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[x] = args
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return impl_ret_untracked(context, builder, sig.return_type, x)
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Index: numba-0.60.0/numba/np/npyfuncs.py
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===================================================================
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--- numba-0.60.0.orig/numba/np/npyfuncs.py
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+++ numba-0.60.0/numba/np/npyfuncs.py
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@@ -16,6 +16,7 @@ from numba.core import typing, types, er
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from numba.core.extending import register_jitable
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from numba.np import npdatetime
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from numba.np.math import cmathimpl, mathimpl, numbers
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+from numba.np.numpy_support import numpy_version
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# some NumPy constants. Note that we could generate some of them using
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# the math library, but having the values copied from npy_math seems to
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@@ -580,29 +581,42 @@ def np_complex_sign_impl(context, builde
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# equivalent to complex sign in NumPy's sign
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# but implemented via selects, balancing the 4 cases.
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_check_arity_and_homogeneity(sig, args, 1)
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- op = args[0]
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- ty = sig.args[0]
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- float_ty = ty.underlying_float
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- ZERO = context.get_constant(float_ty, 0.0)
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- ONE = context.get_constant(float_ty, 1.0)
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- MINUS_ONE = context.get_constant(float_ty, -1.0)
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- NAN = context.get_constant(float_ty, float('nan'))
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- result = context.make_complex(builder, ty)
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- result.real = ZERO
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- result.imag = ZERO
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-
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- cmp_sig = typing.signature(types.boolean, *[ty] * 2)
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- cmp_args = [op, result._getvalue()]
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- arg1_ge_arg2 = np_complex_ge_impl(context, builder, cmp_sig, cmp_args)
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- arg1_eq_arg2 = np_complex_eq_impl(context, builder, cmp_sig, cmp_args)
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- arg1_lt_arg2 = np_complex_lt_impl(context, builder, cmp_sig, cmp_args)
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-
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- real_when_ge = builder.select(arg1_eq_arg2, ZERO, ONE)
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- real_when_nge = builder.select(arg1_lt_arg2, MINUS_ONE, NAN)
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- result.real = builder.select(arg1_ge_arg2, real_when_ge, real_when_nge)
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+ if numpy_version >= (2, 0):
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+ # NumPy >= 2.0.0
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+ def complex_sign(z):
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+ abs = math.hypot(z.real, z.imag)
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+ if abs == 0:
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+ return 0 + 0j
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+ else:
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+ return z / abs
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+
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+ res = context.compile_internal(builder, complex_sign, sig, args)
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+ return impl_ret_untracked(context, builder, sig.return_type, res)
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+ else:
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+ op = args[0]
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+ ty = sig.args[0]
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+ result = context.make_complex(builder, ty)
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+ float_ty = ty.underlying_float
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+
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+ ZERO = context.get_constant(float_ty, 0.0)
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+ ONE = context.get_constant(float_ty, 1.0)
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+ MINUS_ONE = context.get_constant(float_ty, -1.0)
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+ NAN = context.get_constant(float_ty, float('nan'))
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+
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+ result.real = ZERO
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+ result.imag = ZERO
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+ cmp_sig = typing.signature(types.boolean, *[ty] * 2)
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+ cmp_args = [op, result._getvalue()]
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+ arg1_ge_arg2 = np_complex_ge_impl(context, builder, cmp_sig, cmp_args)
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+ arg1_eq_arg2 = np_complex_eq_impl(context, builder, cmp_sig, cmp_args)
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+ arg1_lt_arg2 = np_complex_lt_impl(context, builder, cmp_sig, cmp_args)
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+
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+ real_when_ge = builder.select(arg1_eq_arg2, ZERO, ONE)
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+ real_when_nge = builder.select(arg1_lt_arg2, MINUS_ONE, NAN)
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+ result.real = builder.select(arg1_ge_arg2, real_when_ge, real_when_nge)
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- return result._getvalue()
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+ return result._getvalue()
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########################################################################
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Index: numba-0.60.0/numba/np/ufunc_db.py
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===================================================================
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--- numba-0.60.0.orig/numba/np/ufunc_db.py
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+++ numba-0.60.0/numba/np/ufunc_db.py
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@@ -583,16 +583,58 @@ def _fill_ufunc_db(ufunc_db):
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'f->f': npyfuncs.np_real_floor_impl,
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'd->d': npyfuncs.np_real_floor_impl,
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}
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+ if numpy_version >= (2, 1):
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+ ufunc_db[np.floor].update({
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+ '?->?': numbers.identity_impl,
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+ 'b->b': numbers.identity_impl,
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+ 'B->B': numbers.identity_impl,
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+ 'h->h': numbers.identity_impl,
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+ 'H->H': numbers.identity_impl,
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+ 'i->i': numbers.identity_impl,
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+ 'I->I': numbers.identity_impl,
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+ 'l->l': numbers.identity_impl,
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+ 'L->L': numbers.identity_impl,
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+ 'q->q': numbers.identity_impl,
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+ 'Q->Q': numbers.identity_impl,
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+ })
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ufunc_db[np.ceil] = {
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'f->f': npyfuncs.np_real_ceil_impl,
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'd->d': npyfuncs.np_real_ceil_impl,
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}
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+ if numpy_version >= (2, 1):
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+ ufunc_db[np.ceil].update({
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+ '?->?': numbers.identity_impl,
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+ 'b->b': numbers.identity_impl,
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+ 'B->B': numbers.identity_impl,
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+ 'h->h': numbers.identity_impl,
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+ 'H->H': numbers.identity_impl,
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+ 'i->i': numbers.identity_impl,
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+ 'I->I': numbers.identity_impl,
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+ 'l->l': numbers.identity_impl,
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+ 'L->L': numbers.identity_impl,
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+ 'q->q': numbers.identity_impl,
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+ 'Q->Q': numbers.identity_impl,
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+ })
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ufunc_db[np.trunc] = {
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'f->f': npyfuncs.np_real_trunc_impl,
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'd->d': npyfuncs.np_real_trunc_impl,
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}
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+ if numpy_version >= (2, 1):
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+ ufunc_db[np.trunc].update({
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+ '?->?': numbers.identity_impl,
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+ 'b->b': numbers.identity_impl,
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+ 'B->B': numbers.identity_impl,
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+ 'h->h': numbers.identity_impl,
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+ 'H->H': numbers.identity_impl,
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+ 'i->i': numbers.identity_impl,
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+ 'I->I': numbers.identity_impl,
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+ 'l->l': numbers.identity_impl,
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+ 'L->L': numbers.identity_impl,
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+ 'q->q': numbers.identity_impl,
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+ 'Q->Q': numbers.identity_impl,
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+ })
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ufunc_db[np.fabs] = {
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'f->f': npyfuncs.np_real_fabs_impl,
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Index: numba-0.60.0/numba/tests/test_array_methods.py
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===================================================================
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--- numba-0.60.0.orig/numba/tests/test_array_methods.py
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+++ numba-0.60.0/numba/tests/test_array_methods.py
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@@ -774,13 +774,20 @@ class TestArrayMethods(MemoryLeakMixin,
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check_arr(arr.reshape((2, 3, 4)))
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check_arr(arr.reshape((2, 3, 4)).T)
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check_arr(arr.reshape((2, 3, 4))[::2])
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- for v in (0.0, 1.5, float('nan')):
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- arr = np.array([v]).reshape(())
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- check_arr(arr)
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arr = np.array(["Hello", "", "world"])
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check_arr(arr)
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+ for v in (0.0, 1.5, float('nan')):
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+ arr = np.array([v]).reshape(())
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+ if numpy_version < (2, 1):
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+ check_arr(arr)
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+ else:
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+ with self.assertRaises(ValueError) as raises:
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+ njit((typeof(arr),))(pyfunc)
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+ self.assertEqual(str(raises.exception),
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+ "Calling nonzero on 0d arrays is not allowed. Use np.atleast_1d(scalar).nonzero() instead.")
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+
|
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def test_array_nonzero(self):
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self.check_nonzero(array_nonzero)
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|
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Index: numba-0.60.0/docs/upcoming_changes/9741.highlight.rst
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===================================================================
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--- /dev/null
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+++ numba-0.60.0/docs/upcoming_changes/9741.highlight.rst
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@@ -0,0 +1,4 @@
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+Added Support for NumPy 2.1
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+---------------------------
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+
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+This release adds support for NumPy 2.1 (excluding the NEP-050 semantics).
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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
|
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from numba.core.base import BaseContext
|
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from numba.np import ufunc_db
|
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-from numba.tests.support import expected_failure_np2
|
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|
||||
is32bits = tuple.__itemsize__ == 4
|
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iswindows = sys.platform.startswith('win32')
|
||||
@@ -1696,8 +1695,6 @@ class TestLoopTypesComplex(_LoopTypesTes
|
||||
|
||||
|
||||
TestLoopTypesComplex.autogenerate()
|
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-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):
|
@ -1,3 +1,8 @@
|
||||
-------------------------------------------------------------------
|
||||
Mon Oct 21 13:14:22 UTC 2024 - Markéta Machová <mmachova@suse.com>
|
||||
|
||||
- Add upstream patch numpy21.patch to enable support for NumPy 2.1
|
||||
|
||||
-------------------------------------------------------------------
|
||||
Mon Jul 1 05:10:03 UTC 2024 - Steve Kowalik <steven.kowalik@suse.com>
|
||||
|
||||
|
@ -18,8 +18,8 @@
|
||||
|
||||
%define plainpython python
|
||||
# upper bound is exclusive: min-numpy_ver <= numpy < max_numpy_ver
|
||||
%define min_numpy_ver 1.22
|
||||
%define max_numpy_ver 2.1
|
||||
%define min_numpy_ver 1.24
|
||||
%define max_numpy_ver 2.2
|
||||
|
||||
%{?sle15_python_module_pythons}
|
||||
|
||||
@ -64,6 +64,8 @@ URL: https://numba.pydata.org/
|
||||
Source: https://files.pythonhosted.org/packages/source/n/numba/numba-%{version}.tar.gz
|
||||
# PATCH-FIX-OPENSUSE skip tests failing due to OBS specifics
|
||||
Patch3: skip-failing-tests.patch
|
||||
# PATCH-FIX-UPSTREAM https://github.com/numba/numba/pull/9741 Add Support for NumPy 2.1
|
||||
Patch4: numpy21.patch
|
||||
BuildRequires: %{python_module devel >= 3.9}
|
||||
BuildRequires: %{python_module numpy-devel >= %{min_numpy_ver} with %python-numpy-devel < %{max_numpy_ver}}
|
||||
BuildRequires: %{python_module pip}
|
||||
|
Loading…
Reference in New Issue
Block a user