+1 (non-binding)!
On Mon, Mar 6, 2023 at 9:59 AM Nic Crane <thisis...@gmail.com> wrote:
> +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
> >
>
