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71 lines
2.7 KiB
Python
71 lines
2.7 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 typing import Any, Protocol, Sequence, Union
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import numpy as np
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from jax._src.basearray import Array
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DType = np.dtype
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# TODO(jakevdp, froystig): make OpaqueDType a protocol
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OpaqueDType = 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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# It does not include JAX dtype extensions such as KeyType and others.
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# For now, we use Any to allow scalar types like np.int32 & jnp.int32.
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# TODO(jakevdp) specify these more strictly.
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DTypeLike = Union[Any, str, np.dtype, SupportsDType]
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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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# 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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ArrayLike = Union[
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Array, # JAX array type
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np.ndarray, # NumPy array type
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np.bool_, np.number, # NumPy scalar types
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bool, int, float, complex, # Python scalar types
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]
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