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minor typing fixes in einops.py #431

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minor typing fixes in einops.py #431

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33 changes: 18 additions & 15 deletions einops/einops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,18 +3,22 @@
import string
import typing
from collections import OrderedDict
from typing import Any, Protocol, TypeAlias, TypeVar, cast
from collections.abc import Sequence
from typing import TYPE_CHECKING, Protocol, TypeAlias, TypeVar, cast

from . import EinopsError
from ._backends import get_backend
from .parsing import AnonymousAxis, ParsedExpression, _ellipsis

if TYPE_CHECKING:
import numpy as np


# typing helper, allows not using overloads
class _TensorLike(Protocol):
@property
def shape(self, /) -> typing.Any: ...
def __getitem__(self, arg) -> typing.Any: ...
def __getitem__(self, arg, /) -> typing.Any: ...


Tensor = TypeVar("Tensor", bound=_TensorLike)
Expand All @@ -26,7 +30,7 @@ def __call__(self, tensor: Tensor, axes: tuple[int, ...], /) -> Tensor: ...
def __hash__(self) -> int: ...


Reduction = str | ReductionCallable
Reduction: TypeAlias = str | ReductionCallable
Size: TypeAlias = typing.Any


Expand Down Expand Up @@ -299,6 +303,9 @@ def _apply_recipe_array_api(
return tensor


_Axis: TypeAlias = str | AnonymousAxis


@functools.lru_cache(256)
def _prepare_transformation_recipe(
pattern: str,
Expand Down Expand Up @@ -347,21 +354,21 @@ def _prepare_transformation_recipe(
raise EinopsError(f"Wrong shape: expected >={n_other_dims} dims. Received {ndim}-dim tensor.")
ellipsis_ndim = ndim - n_other_dims
ell_axes = [_ellipsis + str(i) for i in range(ellipsis_ndim)]
left_composition = []
left_composition: list[Sequence[_Axis]] = []
for composite_axis in left.composition:
if composite_axis == _ellipsis:
for axis in ell_axes:
left_composition.append([axis])
else:
left_composition.append(composite_axis)

rght_composition = []
rght_composition: list[Sequence[_Axis]] = []
for composite_axis in rght.composition:
if composite_axis == _ellipsis:
for axis in ell_axes:
rght_composition.append([axis])
else:
group = []
group: list[_Axis] = []
for axis in composite_axis:
if axis == _ellipsis:
group.extend(ell_axes)
Expand All @@ -381,7 +388,7 @@ def _prepare_transformation_recipe(
rght_composition = rght.composition

# parsing all dimensions to find out lengths
axis_name2known_length: OrderedDict[str | AnonymousAxis, int] = OrderedDict()
axis_name2known_length: OrderedDict[_Axis, int] = OrderedDict()
for composite_axis in left_composition:
for axis_name in composite_axis:
if isinstance(axis_name, AnonymousAxis):
Expand Down Expand Up @@ -413,16 +420,16 @@ def _prepare_transformation_recipe(
input_axes_known_unknown = []
# some shapes are inferred later - all information is prepared for faster inference
for composite_axis in left_composition:
known: set[str] = {axis for axis in composite_axis if axis_name2known_length[axis] != _unknown_axis_length}
unknown: set[str] = {axis for axis in composite_axis if axis_name2known_length[axis] == _unknown_axis_length}
known = {axis for axis in composite_axis if axis_name2known_length[axis] != _unknown_axis_length}
unknown = {axis for axis in composite_axis if axis_name2known_length[axis] == _unknown_axis_length}
if len(unknown) > 1:
raise EinopsError(f"Could not infer sizes for {unknown}")
assert len(unknown) + len(known) == len(composite_axis)
input_axes_known_unknown.append(
([axis_name2position[axis] for axis in known], [axis_name2position[axis] for axis in unknown])
)

axis_position_after_reduction: dict[str, int] = {}
axis_position_after_reduction: dict[_Axis, int] = {}
for axis_name in itertools.chain(*left_composition):
if axis_name in rght.identifiers:
axis_position_after_reduction[axis_name] = len(axis_position_after_reduction)
Expand Down Expand Up @@ -748,11 +755,7 @@ def _enumerate_directions(x):
return result


# to avoid importing numpy
np_ndarray = Any


def asnumpy(tensor: Tensor) -> np_ndarray:
def asnumpy(tensor: Tensor) -> "np.ndarray":
"""
Convert a tensor of an imperative framework (i.e. numpy/cupy/torch/jax/etc.) to `numpy.ndarray`

Expand Down
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