Add typing and type annotations for icbc #1453
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Some suggestions 🙂
Given that DeepXDE supports only Python 3.8+, we can use -
from __future__ import annotationsto stay up to date!
I have made a few suggestions regarding the comment above - the rest of the types can be revamped accordingly too!
Also, mypy should be added in the CI to make sure that the types are correct and are being respected throughout the codebase. You can add mypy's configuration in pyproject.toml. This can maybe go in another PR.
(PS: these are just suggestions, the final call would be of DeepXDE's maintainers.)
deepxde/icbc/boundary_conditions.py
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| @@ -14,27 +14,37 @@ | |||
| import numbers | |||
| from abc import ABC, abstractmethod | |||
| from functools import wraps | |||
| from typing import Any, Callable, List, Optional, overload, Tuple, Union | |||
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Given that DeepXDE supports Python 3.8+, you should use -
from __future__ import annotations
from typing import Any, Callable, Optional, overload
deepxde/icbc/boundary_conditions.py
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| outputs: Tensor, | ||
| beg: int, | ||
| end: int, | ||
| aux_var: Union[NDArray[np.float_], None] = None, |
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This should work once the suggestion above is applied.
| aux_var: Union[NDArray[np.float_], None] = None, | |
| aux_var: NDArray[np.float_] | None = None, |
deepxde/icbc/boundary_conditions.py
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| geom: Geometry, | ||
| func: Callable[[NDArray[np.float_]], NDArray[np.float_]], | ||
| on_boundary: Callable[[NDArray[Any], NDArray[Any]], NDArray[np.bool_]], | ||
| component: Union[List[int], int] = 0, |
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| component: Union[List[int], int] = 0, | |
| component: list[int] | int = 0, |
deepxde/types.py
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| # Tensor from any backend | ||
| Tensor = TypeVar("Tensor") | ||
| TensorOrTensors = Union[Tensor, Sequence[Tensor]] |
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| TensorOrTensors = Union[Tensor, Sequence[Tensor]] | |
| TensorOrTensors = Tensor | Sequence[Tensor] | |
deepxde/types.py
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| @@ -0,0 +1,7 @@ | |||
| import numpy as np | |||
| from typing import Callable, Dict, List, Optional, Sequence, Tuple, Union, TypeVar | |||
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| from typing import Callable, Dict, List, Optional, Sequence, Tuple, Union, TypeVar | |
| from __future__ import annotations | |
| from typing import Sequence, TypeVar |
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Thank you for your suggestions, I will change them later 👍
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Good suggestions @Saransh-cpp |
creating an extra file called
types.py, referred from torch.