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This is in preparation for exporting this to `jax.typing.DTypeLike`. Currently this is effectively just Any, and we want to make certain it's a meaningful type before exporting. PiperOrigin-RevId: 572260744
80 lines
2.9 KiB
Python
80 lines
2.9 KiB
Python
# Copyright 2022 The JAX Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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`jax._src.typing`: JAX type annotations
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---------------------------------------
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This submodule is a work in progress; when we finalize the contents here, it will be
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exported at `jax.typing`. Until then, the contents here should be considered unstable
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and may change without notice.
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To see the proposal that led to the development of these tools, see
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https://github.com/google/jax/pull/11859/.
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"""
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from __future__ import annotations
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from collections.abc import Sequence
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from typing import Any, Protocol, Union
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import numpy as np
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from jax._src.basearray import (
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Array as Array,
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ArrayLike as ArrayLike,
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)
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DType = np.dtype
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# TODO(jakevdp, froystig): make ExtendedDType a protocol
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ExtendedDType = Any
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class SupportsDType(Protocol):
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@property
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def dtype(self) -> DType: ...
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# DTypeLike is meant to annotate inputs to np.dtype that return
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# a valid JAX dtype. It's different than numpy.typing.DTypeLike
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# because JAX doesn't support objects or structured dtypes.
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# Unlike np.typing.DTypeLike, we exclude None, and instead require
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# explicit annotations when None is acceptable.
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# TODO(jakevdp): consider whether to add ExtendedDtype to the union.
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DTypeLike = Union[
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str, # like 'float32', 'int32'
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type[Any], # like np.float32, np.int32, float, int
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np.dtype, # like np.dtype('float32'), np.dtype('int32')
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SupportsDType, # like jnp.float32, jnp.int32
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]
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# Shapes are tuples of dimension sizes, which are normally integers. We allow
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# modules to extend the set of dimension sizes to contain other types, e.g.,
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# symbolic dimensions in jax2tf.shape_poly.DimVar and masking.Poly.
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DimSize = Union[int, Any] # extensible
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Shape = Sequence[DimSize]
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class DuckTypedArray(Protocol):
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@property
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def dtype(self) -> DType: ...
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@property
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def shape(self) -> Shape: ...
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# Array is a type annotation for standard JAX arrays and tracers produced by
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# core functions in jax.lax and jax.numpy; it is not meant to include
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# future non-standard array types like KeyArray and BInt. It is imported above.
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# ArrayLike is a Union of all objects that can be implicitly converted to a standard
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# JAX array (i.e. not including future non-standard array types like KeyArray and BInt).
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# It's different than np.typing.ArrayLike in that it doesn't accept arbitrary sequences,
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# nor does it accept string data.
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