transonic issueshttps://foss.heptapod.net/fluiddyn/transonic/-/issues2020-11-29T20:43:19Zhttps://foss.heptapod.net/fluiddyn/transonic/-/issues/31Transonic plugin framework2020-11-29T20:43:19ZBitbucket ImporterTransonic plugin framework*Created originally on Bitbucket by [avmo (Ashwin Vishnu)](https://bitbucket.org/%7Bbd72905e-cf99-4847-84c2-998104370f6e%7D/)*
Starting an issue to discuss possible plugin APIs*Created originally on Bitbucket by [avmo (Ashwin Vishnu)](https://bitbucket.org/%7Bbd72905e-cf99-4847-84c2-998104370f6e%7D/)*
Starting an issue to discuss possible plugin APIshttps://foss.heptapod.net/fluiddyn/transonic/-/issues/9Type hints: ShapeVar2020-02-12T22:35:13ZBitbucket ImporterType hints: ShapeVar*Created originally on Bitbucket by [paugier (Pierre Augier)](https://bitbucket.org/%7Beb327c54-cadd-4fce-9edd-f8fe047a9b93%7D/)*
```
from transonic import boost, Type, NDim, Shape, Array
T = Type(int, float)
# here the shape of ...*Created originally on Bitbucket by [paugier (Pierre Augier)](https://bitbucket.org/%7Beb327c54-cadd-4fce-9edd-f8fe047a9b93%7D/)*
```
from transonic import boost, Type, NDim, Shape, Array
T = Type(int, float)
# here the shape of the array is only defined with the ShapeVar
A = Array[T, Shape("[3, :]", "[3, :, :]", "[::, ::]", "[::, ::, ::]")]
@boost
def compute(a: A, b: A, c: T):
return a + b
# if there is a NDimVar, we can use the ellipsis
A1 = Array[T, NDim(1, 3), Shape("[3, ...]", "[::, ...]")]
@boost
def compute1(a: A1, b: A1, c: T):
return c * (a + b)
```https://foss.heptapod.net/fluiddyn/transonic/-/issues/39Typing improvements: annotations and numpy.typing2021-02-08T09:45:40ZAshwin V. MohananTyping improvements: annotations and numpy.typingThere are two major updates:
- Type hints can be more concise due to two new PEPs. This may be handled by the AST parser, but should be checked.
- Numpy officially supports type-annotations starting v1.20. At some point we should transi...There are two major updates:
- Type hints can be more concise due to two new PEPs. This may be handled by the AST parser, but should be checked.
- Numpy officially supports type-annotations starting v1.20. At some point we should transition `transonic.typing` towards that / support them additionally.
See: https://www.scivision.dev/mypy-pep-585-604/