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Dask Array's constant pad coerces array to NumPy ndarray

See original GitHub issue

Currently Dask Array’s pad (when using the constant mode) may end up coercing array data of a different array type to a NumPy ndarray. For example, the following code will result in a NumPy ndarray.

a_gpu_pad = da.pad(a_gpu, 1, "constant")
a_gpu_pad.compute()

This still happens if we try to set the constant_values differently. If we provide a 0-D array, we run into issue ( https://github.com/dask/dask/issues/4841 ).

Issue Analytics

State:
Created 4 years ago
Comments:8 (7 by maintainers)

Top GitHub Comments

1reaction

pentschevcommented, Jun 7, 2019

No, unfortunately da.pad relies on da.asarray, which in turn relies on np.asarray. We’ve started a discussion on how to deal with those cases in #4883.

If this particular case (constant padding) is needed immediately, I think we could use *_like functions instead, but to solve pad more generally we will require to deal with the cases I mentioned above.

0reactions

pentschevcommented, Nov 16, 2020

@mrocklin @jakirkham just wanted to ping this issue to get help promote it.

Any tips on solving the coercion issue for cupy arrays in the cupy_backed_array.map_overlap(..., boundary=0.) case?

The original issue here with da.pad is going to be resolved by https://github.com/dask/dask/pull/6738. However, your issue with map_overlap (that internally relies on map_blocks) is probably solved by passing meta=, please see https://github.com/dask/dask/blob/8d622ad81162245d5e7663522b9721df5b23e9f4/dask/array/core.py#L486-L495

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