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License: MIT License
Data and tooling to compare the API surfaces of various array libraries.
License: MIT License
Add a table which maps each NumPy API to a higher-level category/group.
See rnumpy for initial ideas.
Add Jupyter notebook(s) which loads datasets and performs analysis.
We at ONNX are working on the roadmap and I'm proposing that we adopt the numpy array API definition and eventually the array API standard from the outcome of this work group. ONNX is a model exchange standard for the deep learning frameworks. The array API comparison exercise here is very helpful and it would be great if we could include the ONNX in the comparison here.
The definition of array API functions can be found here.
This will allow for aggregating usage data to represent a particular kind of operation (e.g., transpose
, mean
, etc).
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