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Make AUTO a PEP661 sentinel #1011

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14 changes: 11 additions & 3 deletions loopy/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,7 @@

import os
from typing import TYPE_CHECKING
from warnings import warn

from pytools import strtobool

Expand Down Expand Up @@ -217,7 +218,7 @@
from loopy.translation_unit import TranslationUnit, for_each_kernel, make_program
from loopy.type_inference import infer_unknown_types
from loopy.types import LoopyType, NumpyType, ToLoopyTypeConvertible, to_loopy_type
from loopy.typing import PreambleGenerator, auto
from loopy.typing import AUTO, PreambleGenerator
from loopy.version import MOST_RECENT_LANGUAGE_VERSION, VERSION


Expand All @@ -226,6 +227,7 @@


__all__ = [
"AUTO",
"MOST_RECENT_LANGUAGE_VERSION",
"VERSION",
"ASTBuilderBase",
Expand Down Expand Up @@ -308,7 +310,6 @@
"allocate_temporaries_for_base_storage",
"assignment_to_subst",
"assume",
"auto",
"auto_test_vs_ref",
"buffer_array",
"c_preprocess",
Expand Down Expand Up @@ -587,7 +588,7 @@ def make_copy_kernel(new_dim_tags, old_dim_tags=None):
"output[%s] = input[%s]"
% (command_indices, command_indices),
lang_version=MOST_RECENT_LANGUAGE_VERSION,
default_offset=auto)
default_offset=AUTO)

result = tag_array_axes(result, "input", old_dim_tags)
result = tag_array_axes(result, "output", new_dim_tags)
Expand Down Expand Up @@ -707,4 +708,11 @@ def _set_up_default_target():
# }}}


def __getattr__(name: str):
if name == "auto":
warn("auto is deprecated and will be removed in 2027.x. Use AUTO.",
DeprecationWarning, stacklevel=2)
return AUTO


# vim: foldmethod=marker
24 changes: 12 additions & 12 deletions loopy/check.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,7 +72,7 @@
check_each_kernel,
)
from loopy.type_inference import TypeReader
from loopy.typing import auto, not_none
from loopy.typing import AUTO, not_none


if TYPE_CHECKING:
Expand Down Expand Up @@ -253,7 +253,7 @@ def ensure_depends_only_on_arguments(
what = f"offset of argument '{arg.name}'"
if arg.offset is None:
continue
if arg.offset is auto:
if arg.offset is AUTO:
pass
elif isinstance(arg.offset, (int, np.integer, ExpressionNode, str)):
ensure_depends_only_on_arguments(what, arg.offset)
Expand All @@ -270,7 +270,7 @@ def ensure_depends_only_on_arguments(
if isinstance(dim_tag, FixedStrideArrayDimTag):
what = (f"stride for axis {iaxis+1} (1-based) of "
f"of argument '{arg.name}'")
if dim_tag.stride is auto:
if dim_tag.stride is AUTO:
pass
elif isinstance(
dim_tag.stride, (int, np.integer, ExpressionNode)):
Expand All @@ -291,7 +291,7 @@ def ensure_depends_only_on_arguments(

for tv in kernel.temporary_variables.values():
what = f"offset of temporary '{tv.name}'"
if tv.offset is auto:
if tv.offset is AUTO:
pass
elif isinstance(tv.offset, (int, np.integer, ExpressionNode, str)):
ensure_depends_only_on_arguments(what, tv.offset)
Expand All @@ -303,7 +303,7 @@ def ensure_depends_only_on_arguments(
if isinstance(dim_tag, FixedStrideArrayDimTag):
what = ("axis stride for axis "
f"{iaxis+1} (1-based) of temporary '{tv.name}'")
if dim_tag.stride is auto:
if dim_tag.stride is AUTO:
raise LoopyError(f"The {what}" f" is 'auto', "
"which is not allowed.")
elif isinstance(dim_tag.stride, (int, np.integer, ExpressionNode)):
Expand Down Expand Up @@ -345,9 +345,9 @@ def map_subscript(self, expr):

def _check_for_integer_subscript_indices_inner(kernel, callables_table):

from loopy.kernel.data import auto
if any(arg.dtype in [None, auto] for arg in kernel.args) or (
any(tv.dtype in [None, auto]
from loopy.kernel.data import AUTO
if any(arg.dtype in [None, AUTO] for arg in kernel.args) or (
any(tv.dtype in [None, AUTO]
for tv in kernel.temporary_variables.values())):
# some types are not resolved => do not check.
return
Expand Down Expand Up @@ -571,11 +571,11 @@ def check_for_unused_inames(kernel: LoopKernel) -> None:

def _is_racing_iname_tag(tv: TemporaryVariable, tag: InameImplementationTag) -> bool:
from loopy.kernel.data import (
AUTO,
AddressSpace,
ConcurrentTag,
GroupInameTag,
LocalInameTagBase,
auto,
)

if tv.address_space == AddressSpace.PRIVATE:
Expand All @@ -591,7 +591,7 @@ def _is_racing_iname_tag(tv: TemporaryVariable, tag: InameImplementationTag) ->
elif tv.address_space == AddressSpace.GLOBAL:
return isinstance(tag, ConcurrentTag)

elif tv.address_space == auto:
elif tv.address_space == AUTO:
raise LoopyError("scope of temp var '%s' has not yet been"
"determined" % tv.name)

Expand Down Expand Up @@ -1045,7 +1045,7 @@ def declares_nosync_with(kernel, var_address_space, dep_a, dep_b):
return ab_nosync and ba_nosync


def _get_address_space(kernel: LoopKernel, var: str) -> AddressSpace | type[auto]:
def _get_address_space(kernel: LoopKernel, var: str) -> AddressSpace | AUTO:
from loopy.kernel.data import ArrayArg, ValueArg
if var in kernel.temporary_variables:
address_space = kernel.temporary_variables[var].address_space
Expand Down Expand Up @@ -1659,7 +1659,7 @@ def check_that_shapes_and_strides_are_arguments(kernel: LoopKernel) -> None:

for dim_tag in arg.dim_tags:
if isinstance(dim_tag, FixedStrideArrayDimTag):
if dim_tag.stride is lp.auto:
if dim_tag.stride is lp.AUTO:
continue

deps = get_dependencies(dim_tag.stride)
Expand Down
56 changes: 28 additions & 28 deletions loopy/kernel/array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,7 @@
from loopy.diagnostic import LoopyError
from loopy.symbolic import flatten
from loopy.types import LoopyType
from loopy.typing import ShapeType, auto, is_integer
from loopy.typing import AUTO, ShapeType, is_integer


if TYPE_CHECKING:
Expand Down Expand Up @@ -160,7 +160,7 @@ def stringify(self, include_target_axis):
result += "N%d:" % self.layout_nesting_level

import loopy as lp
if self.stride is lp.auto:
if self.stride is lp.AUTO:
result += "stride:auto"
else:
result += "stride:"+str(self.stride)
Expand All @@ -173,21 +173,21 @@ def __str__(self):
return self.stringify(True)

def map_expr(self, mapper):
from loopy.kernel.data import auto
from loopy.kernel.data import AUTO

if self.stride is auto:
if self.stride is AUTO:
# lp.auto not an expr => do not map
return self

return self.copy(stride=mapper(self.stride))

def depends_on(self):
from loopy.kernel.data import auto
from loopy.kernel.data import AUTO
from loopy.symbolic import DependencyMapper
if self.stride is auto:
if self.stride is AUTO:
return frozenset()

return DependencyMapper(composite_leaves=auto)(self.stride)
return DependencyMapper(composite_leaves=AUTO)(self.stride)


class ComputedStrideArrayDimTag(_StrideArrayDimTagBase):
Expand Down Expand Up @@ -310,7 +310,7 @@ def _parse_array_dim_tag(tag, default_target_axis, nesting_levels):
return (
has_explicit_nesting_level, is_optional,
FixedStrideArrayDimTag(
lp.auto, target_axis,
lp.AUTO, target_axis,
layout_nesting_level=nesting_level))
else:
from loopy.symbolic import parse
Expand Down Expand Up @@ -489,7 +489,7 @@ def convert_computed_to_fixed_dim_tags(
name: str,
num_user_axes: int | None,
num_target_axes: int,
shape: ShapeType | type[auto] | None,
shape: ShapeType | AUTO | None,
dim_tags: Sequence[ArrayDimImplementationTag],
) -> Sequence[ArrayDimImplementationTag] | None:

Expand Down Expand Up @@ -544,7 +544,7 @@ def convert_computed_to_fixed_dim_tags(
if vector_dim is None:
stride_so_far = 1
else:
if shape is None or shape is lp.auto:
if shape is None or shape is lp.AUTO:
# unable to normalize without known shape
return None

Expand Down Expand Up @@ -581,7 +581,7 @@ def convert_computed_to_fixed_dim_tags(
target_axis=dim_tag.target_axis,
layout_nesting_level=dim_tag.layout_nesting_level)

if shape is None or shape is lp.auto:
if shape is None or shape is lp.AUTO:
# unable to normalize without known shape
return None
assert isinstance(shape, tuple)
Expand All @@ -601,7 +601,7 @@ def convert_computed_to_fixed_dim_tags(
elif isinstance(dim_tag, FixedStrideArrayDimTag):
stride_so_far = dim_tag.stride

if stride_so_far is lp.auto:
if stride_so_far is lp.AUTO:
stride_so_far = None

else:
Expand All @@ -617,20 +617,20 @@ def convert_computed_to_fixed_dim_tags(
# {{{ array base class (for arguments and temporary arrays)

ToShapeLikeConvertible: TypeAlias = (tuple[Expression | str, ...]
| Expression | type[auto] | str | tuple[str, ...])
| Expression | AUTO | str | tuple[str, ...])


def _parse_shape_or_strides(
x: ToShapeLikeConvertible,
) -> ShapeType | type[auto]:
) -> ShapeType | AUTO:
from pymbolic import parse

if x == "auto":
raise ValueError("use of 'auto' as a shape or stride won't work "
"any more--use loopy.auto instead")

if x is auto:
return auto
if x is AUTO:
return AUTO

x_parsed = x if not isinstance(x, str) else parse(x)

Expand All @@ -640,7 +640,7 @@ def _parse_shape_or_strides(
if isinstance(x_parsed, tuple):
x_tup: tuple[Expression | str, ...] = x_parsed
else:
assert x_parsed is not auto
assert x_parsed is not AUTO
x_tup = (cast("Expression", x_parsed),)

def parse_arith(x: Expression | str) -> ArithmeticExpression:
Expand Down Expand Up @@ -690,7 +690,7 @@ class ArrayBase(ImmutableRecord, Taggable):
cannot be performed without knowledge of the exact *dtype*.
"""

shape: ShapeType | type[auto] | None
shape: ShapeType | AUTO | None
"""
May be one of the following:

Expand Down Expand Up @@ -818,11 +818,11 @@ def __init__(self, name, dtype=None, shape=None, dim_tags=None, offset=0,
dtype = to_loopy_type(dtype, allow_auto=True, allow_none=True,
for_atomic=for_atomic)

if dtype is lp.auto:
if dtype is lp.AUTO:
raise ValueError("dtype may not be lp.auto")

strides_known = strides is not None and strides is not lp.auto
shape_known = shape is not None and shape is not lp.auto
strides_known = strides is not None and strides is not lp.AUTO
shape_known = shape is not None and shape is not lp.AUTO

if strides_known:
strides = _parse_shape_or_strides(strides)
Expand Down Expand Up @@ -1001,15 +1001,15 @@ def stringify(self, include_typename):
if include_typename:
info_entries.append(type(self).__name__)

assert self.dtype is not lp.auto
assert self.dtype is not lp.AUTO

type_str = "<auto/runtime>" if self.dtype is None else str(self.dtype)

info_entries.append("type: %s" % type_str)

if self.shape is None:
info_entries.append("shape: unknown")
elif self.shape is lp.auto:
elif self.shape is lp.AUTO:
info_entries.append("shape: auto")
else:
# shape is iterable
Expand Down Expand Up @@ -1067,8 +1067,8 @@ def num_target_axes(self):
return len(target_axes)

def num_user_axes(self, require_answer=True):
from loopy import auto
if self.shape not in (None, auto):
from loopy import AUTO
if self.shape is not None and self.shape is not AUTO:
return len(self.shape)
if self.dim_tags is not None:
return len(self.dim_tags)
Expand All @@ -1086,7 +1086,7 @@ def map_exprs(self, mapper: Callable[[Expression], Expression]) -> Self:
kwargs: dict[str, Any] = {}
import loopy as lp

if self.shape is not None and self.shape is not lp.auto:
if self.shape is not None and self.shape is not lp.AUTO:
assert isinstance(self.shape, tuple)

def none_pass_mapper(s: Expression | None) -> Expression | None:
Expand Down Expand Up @@ -1234,7 +1234,7 @@ def _apply_offset(sub: ArithmeticExpression, ary: ArrayBase) -> ArithmeticExpres
# is declared.
return sub

if ary.offset is lp.auto:
if ary.offset is lp.AUTO:
raise AssertionError(
f"Offset for '{ary.name}' should have been replaced "
"with an actual argument by "
Expand Down Expand Up @@ -1346,7 +1346,7 @@ def eval_expr_assert_integer_constant(i, expr) -> int:
"vector (%d)"
% (ary.name, i, dim_tag.stride, vector_size))

elif stride is lp.auto:
elif stride is lp.AUTO:
raise AssertionError(
f"Stride for axis {i+1} (1-based) of "
"'{array_name}' should have been replaced "
Expand Down
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