[bug] [lang] Fix copyback for fortran contiguous numpy arrays #6376
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fixes taichi-dev#6305 Taichi kernel assumes input external array are row major / c_contiguous for now so this PR throws an error message when the input numpy array isn't contiguous. Note that we only supports inplace update for c_contiguous numpy arrays but for historical reason support for f_contiguous array was added via copying (`ascontiguousarray()`) as well, thus this PR tries to preserve the support to avoid breaking old code. Also the support for f_contiguous numpy array was halfly done since `ascontiguousarray()` may return a new numpy array, Taichi kernels just read/write on the copied array and don't copy the values back to the original numpy array. This PR fixes the bug mentioned above by adding a callback function to copy values back, although copying behavior isn't efficient it guarantees correctness so that we can improve it in the future.
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ailzhang
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Oct 20, 2022
#6390) Reverts #6376 since it broke examples in release tests https://github.com/taichi-dev/taichi/actions/runs/3286644295/jobs/5416572173
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fixes #6305
Taichi kernel assumes input external array are row major / c_contiguous for now so this PR throws an error message when the input numpy array isn't contiguous.
Note that we only supports inplace update for c_contiguous numpy arrays but for historical reason support for f_contiguous array was added via copying (
ascontiguousarray()) as well, thus this PR tries to preserve the support to avoid breaking old code.Also the support for f_contiguous numpy array was halfly done since
ascontiguousarray()may return a new numpy array, Taichi kernels just read/write on the copied array and don't copy the values back to the original numpy array.This PR fixes the bug mentioned above by adding a callback function to copy values back, although copying behavior isn't efficient it guarantees correctness so that we can improve it in the future.
Issue: #
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