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Merged
sklam merged 13 commits into from
May 26, 2022
Merged

min() and max() support for np.datetime and np.timedelta #7836

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a305435
Added tests
benwilliamgraham Feb 11, 2022
9def383
Added more tests
benwilliamgraham Feb 11, 2022
75c23bc
Fixed array max/min
benwilliamgraham Feb 15, 2022
42ee62e
Fixed return/continue
benwilliamgraham Feb 15, 2022
c973f46
Fixed min/max reduction
benwilliamgraham Feb 16, 2022
8a7e68c
Added reductions
benwilliamgraham Feb 17, 2022
45e82c4
Reorg
benwilliamgraham Feb 18, 2022
b7d3048
Update numba/core/typing/npdatetime.py
benwilliamgraham Feb 18, 2022
dd32396
Update numba/np/npdatetime.py
benwilliamgraham Feb 18, 2022
07276e0
Fixed max
benwilliamgraham Feb 18, 2022
7b0e387
Removed unenesary typing
benwilliamgraham Feb 23, 2022
ba99506
Adressed comments
benwilliamgraham May 18, 2022
4017346
Update numba/core/typing/builtins.py
benwilliamgraham May 24, 2022
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Fixed min/max reduction
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@benwilliamgraham
benwilliamgraham committed Feb 16, 2022
commit c973f46b2dea9ecac48420f834d78d58134c8f43
106 changes: 55 additions & 51 deletions numba/parfors/parfor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,13 +24,15 @@
from contextlib import contextmanager
import operator

from llvmlite import ir as lir
from numba.core.imputils import impl_ret_untracked
import numba.core.ir
from numba.core import types, typing, utils, errors, ir, analysis, postproc, rewrites, typeinfer, config, ir_utils
from numba import prange, pndindex
from numba.np.numpy_support import as_dtype, numpy_version
from numba.core.typing.templates import infer_global, AbstractTemplate
from numba.stencils.stencilparfor import StencilPass
from numba.core.extending import register_jitable
from numba.core.extending import register_jitable, lower_builtin

from numba.core.ir_utils import (
mk_unique_var,
Expand Down Expand Up @@ -121,6 +123,26 @@ class internal_prange(object):
def __new__(cls, *args):
return range(*args)

def _get_nat(typ):
return types.int64.minval

@infer_global(_get_nat)
@infer_global(_get_nat)
class _NatInfer(AbstractTemplate):
def generic(self, args, kws):
assert not kws
assert len(args) == 1
assert isinstance(args[0], (types.DType))
return signature(args[0].dtype, *args)

@lower_builtin(_get_nat, types.DType)
def lower_get_nat(context, builder, sig, args):
bw = 64
lty = lir.IntType(bw)
val = types.int64.minval
res = lir.Constant(lty, val)
return impl_ret_untracked(context, builder, lty, res)

def min_parallel_impl(return_type, arg):
# XXX: use prange for 1D arrays since pndindex returns a 1-tuple instead of
# integer. This causes type and fusion issues.
Expand All @@ -129,31 +151,22 @@ def min_1(in_arr):
return in_arr[()]
elif arg.ndim == 1:
if isinstance(arg.dtype, (types.NPDatetime, types.NPTimedelta)):
# starting in NumPy 1.18, NaT is always returned if it is in the array
# prior to 1.18, NaT is skipped unless it is the only value in the array
if numpy_version >= (1, 18):
def min_1(in_arr):
numba.parfors.parfor.init_prange()
min_checker(len(in_arr))
val = numba.cpython.builtins.get_type_max_value(in_arr.dtype)
for i in numba.parfors.parfor.internal_prange(len(in_arr)):
if np.isnat(in_arr[i]):
val = in_arr[i]
elif not np.isnat(val):
val = min(val, in_arr[i])
return val
else:
def min_1(in_arr):
numba.parfors.parfor.init_prange()
min_checker(len(in_arr))
# assign val initially to NaT (int64 min)
val = types.int64.minval
for i in numba.parfors.parfor.internal_prange(len(in_arr)):
if np.isnat(val):
val = in_arr[i]
else:
val = min(val, in_arr[i])
return val
# NaT is always returned if it is in the array
def min_1(in_arr):
numba.parfors.parfor.init_prange()
min_checker(len(in_arr))
val = numba.cpython.builtins.get_type_max_value(in_arr.dtype)
has_nat = False
for i in numba.parfors.parfor.internal_prange(len(in_arr)):
has_nat = has_nat | np.isnat(in_arr[i])

if has_nat:
return _get_nat(in_arr.dtype)

for i in numba.parfors.parfor.internal_prange(len(in_arr)):
val = min(val, in_arr[i])

return val
else:
def min_1(in_arr):
numba.parfors.parfor.init_prange()
Expand All @@ -178,31 +191,22 @@ def max_1(in_arr):
return in_arr[()]
elif arg.ndim == 1:
if isinstance(arg.dtype, (types.NPDatetime, types.NPTimedelta)):
# starting in NumPy 1.18, NaT is always returned if it is in the array
# prior to 1.18, NaT is skipped unless it is the only value in the array
if numpy_version >= (1, 18):
def min_1(in_arr):
numba.parfors.parfor.init_prange()
max_checker(len(in_arr))
val = numba.cpython.builtins.get_type_min_value(in_arr.dtype)
for i in numba.parfors.parfor.internal_prange(len(in_arr)):
if np.isnat(in_arr[i]):
val = in_arr[i]
elif not np.isnat(val):
val = max(val, in_arr[i])
return val
else:
def min_1(in_arr):
numba.parfors.parfor.init_prange()
max_checker(len(in_arr))
# assign val initially to NaT (int64 min)
val = types.int64.minval
for i in numba.parfors.parfor.internal_prange(len(in_arr)):
if np.isnat(val):
val = in_arr[i]
else:
val = max(val, in_arr[i])
return val
# NaT is always returned if it is in the array
def max_1(in_arr):
numba.parfors.parfor.init_prange()
max_checker(len(in_arr))
val = numba.cpython.builtins.get_type_min_value(in_arr.dtype)
has_nat = False
for i in numba.parfors.parfor.internal_prange(len(in_arr)):
has_nat = has_nat | np.isnat(in_arr[i])

if has_nat:
return _get_nat(in_arr.dtype)

for i in numba.parfors.parfor.internal_prange(len(in_arr)):
val = max(val, in_arr[i])

return val
else:
def max_1(in_arr):
numba.parfors.parfor.init_prange()
Expand Down
9 changes: 1 addition & 8 deletions numba/tests/test_npdatetime.py
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Original file line number Diff line number Diff line change
Expand Up @@ -997,6 +997,7 @@ def impl(arr):
DT("2004-12-07", "ns"),
]),
np.array([
DT("1971-02-02", "ns"),
DT("NaT", "ns"),
]),
np.array([
Expand Down Expand Up @@ -1069,10 +1070,6 @@ def test_max_method(self):

@skip_parfors_unsupported
def test_min_func_parallel(self):
self._test_min_max(min, True, False)

@skip_parfors_unsupported
def test_np_min_func_parallel(self):
self._test_min_max(np.min, True, False)

@skip_parfors_unsupported
Expand All @@ -1081,10 +1078,6 @@ def test_min_method_parallel(self):

@skip_parfors_unsupported
def test_max_func_parallel(self):
self._test_min_max(max, True, False)

@skip_parfors_unsupported
def test_np_max_func_parallel(self):
self._test_min_max(np.max, True, False)

@skip_parfors_unsupported
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