numba affords the developer the ability to overload functions, methods and attributes, as well as implement intrinsics https://numba.readthedocs.io/en/stable/extending/index.html
I've found this very useful for CPU targets and it seems that similar functionality is available in numba CUDA:
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def overload( |
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func, |
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jit_options=None, |
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strict=True, |
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inline="never", |
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prefer_literal=False, |
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target="cuda", |
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**kwargs, |
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): |
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""" |
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A decorator marking the decorated function as typing and implementing |
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*func* in nopython mode. |
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The decorated function will have the same formal parameters as *func* |
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and be passed the Numba types of those parameters. It should return |
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a function implementing *func* for the given types. |
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Here is an example implementing len() for tuple types:: |
but it doesn't appear in the documentation https://nvidia.github.io/numba-cuda/index.html. Is this functionality supported?
numba affords the developer the ability to overload functions, methods and attributes, as well as implement intrinsics https://numba.readthedocs.io/en/stable/extending/index.html
I've found this very useful for CPU targets and it seems that similar functionality is available in numba CUDA:
numba-cuda/numba_cuda/numba/cuda/extending.py
Lines 133 to 150 in da60f0a
but it doesn't appear in the documentation https://nvidia.github.io/numba-cuda/index.html. Is this functionality supported?