+1

On Mon, 6 Mar 2023 at 12:41, Alenka Frim <ale...@voltrondata.com.invalid>
wrote:

> Hi all,
>
> I am starting a new voting thread with this email as the first voting
> thread [1] opened up new
> comments and suggestions and we wanted to take time to see how that
> evolves.
>
> *I would like to propose we vote on adding the fixed shape tensor canonical
> extension type*
> *with the following specification:*
>
> Fixed shape tensor
> ==================
>
> * Extension name: `arrow.fixed_shape_tensor`.
>
> * The storage type of the extension: ``FixedSizeList`` where:
>
>   * **value_type** is the data type of individual tensor elements.
>   * **list_size** is the product of all the elements in tensor shape.
>
> * Extension type parameters:
>
>   * **value_type** = the Arrow data type of individual tensor elements.
>   * **shape** = the physical shape of the contained tensors
>     as an array.
>
>   Optional parameters describing the logical layout:
>
>   * **dim_names** = explicit names to tensor dimensions
>     as an array. The length of it should be equal to the shape
>     length and equal to the number of dimensions.
>
>     ``dim_names`` can be used if the dimensions have well-known
>     names and they map to the physical layout (row-major).
>
>   * **permutation**  = indices of the desired ordering of the
>     original dimensions, defined as an array.
>
>     The indices contain a permutation of the values [0, 1, .., N-1] where
>     N is the number of dimensions. The permutation indicates which
>     dimension of the logical layout corresponds to which dimension of the
>     physical tensor (the i-th dimension of the logical view corresponds
>     to the dimension with number ``permutations[i]`` of the physical
> tensor).
>
>     Permutation can be useful in case the logical order of
>     the tensor is a permutation of the physical order (row-major).
>
>     When logical and physical layout are equal, the permutation will always
>     be ([0, 1, .., N-1]) and can therefore be left out.
>
> * Description of the serialization:
>
>   The metadata must be a valid JSON object including shape of
>   the contained tensors as an array with key **"shape"** plus optional
>   dimension names with keys **"dim_names"** and ordering of the
>   dimensions with key **"permutation"**.
>
>   - Example: ``{ "shape": [2, 5]}``
>   - Example with ``dim_names`` metadata for NCHW ordered data:
>
>     ``{ "shape": [100, 200, 500], "dim_names": ["C", "H", "W"]}``
>
>   - Example of permuted 3-dimensional tensor:
>
>     ``{ "shape": [100, 200, 500], "permutation": [2, 0, 1]}``
>
>     This is the physical layout shape and the the shape of the logical
>     layout would in this case be ``[500, 100, 200]``.
>
> .. note::
>
>   Elements in a fixed shape tensor extension array are stored
>   in row-major/C-contiguous order.
>
> * The specification is submitted as a PR [2] to Canonical Extension Types
> document under the
>    format specifications directory [3].
>
> There are also two implementations submitted to Apache Arrow repository:
> * C++ implementation of the proposed specification [4]
> * Python example implementation of the proposed specification and usage
> (only illustrative) [5]
>
>
> The vote will be open for at least 72 hours.
>
> [ ] +1 Accept this proposal
> [ ] +0
> [ ] -1 Do not accept this proposal because...
>
>
> Regards, Alenka
>
> [1]: https://lists.apache.org/thread/3cj0cr44hg3t2rn0kxly8td82yfob1nd
> [2]: https://github.com/apache/arrow/pull/33925/files
> [3]:
>
> https://github.com/apache/arrow/blob/main/docs/source/format/CanonicalExtensions.rst
>
> [4]: https://github.com/apache/arrow/pull/8510/files
> [5]: https://github.com/apache/arrow/pull/33948/files
>

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