[
https://issues.apache.org/jira/browse/ARROW-8714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17223622#comment-17223622
]
Joris Van den Bossche commented on ARROW-8714:
----------------------------------------------
bq. I also had another thought, if the shape for each tensor added an
additional outer dimension to represent how many records are in each tensor,
that would allow us to use a single tensor extension type for both variable and
constant dimensions.
To clarify, this is only about constant vs variable _dimensions_, and not about
constant _shape_ ?
My understanding was that ARROW-1614 is also about constant shape (although the
title only says dimension), and then I don't see how that would be possible to
combine in the way described?
> [C++] Add a Tensor logical value type with varying dimensions, implemented
> using ExtensionType
> ----------------------------------------------------------------------------------------------
>
> Key: ARROW-8714
> URL: https://issues.apache.org/jira/browse/ARROW-8714
> Project: Apache Arrow
> Issue Type: Improvement
> Components: C++, Format
> Reporter: Christian Hudon
> Priority: Major
>
> Support for tensor in Table, RecordBatch, etc. where each row is a tensor of
> a different shape (e.g images of different sizes), but of the same underlying
> type (e.g. int32). Implemented as an ExtensionType, so no need to change the
> format.
> I don't see needing each row being a tensor with a different number of
> dimensions, so if the implementation for that falls out easily of the use
> case with each row in the table having a tensor with the same number of
> dimensions, great. If it adds a lot of complexity, that case would be
> postponed.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
