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https://issues.apache.org/jira/browse/ARROW-10101?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17205724#comment-17205724
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David Li commented on ARROW-10101:
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Thanks [[email protected]]. I'm not aware of an existing model. Honestly,
my intent here is not really to provide an API to manipulate them in Java, but
to just make it possible to round-trip them and convert to/from other APIs,
hence why the methods on this Tensor are pretty sparse.
A brief search turns up these:
* nd4j - looks abandoned - [https://github.com/deeplearning4j/nd4j] - but it
seems to be based on an off-heap buffer model like Arrow with shape/stride info
* djl.ai from AWSLabs -
[https://github.com/awslabs/djl/tree/master/api/src/main/java/ai/djl/ndarray] -
seems to be ByteBuffer based with shape/stride info
* Vectorz - double[] based -
[https://github.com/mikera/vectorz/blob/develop/src/main/java/mikera/arrayz/impl/BaseNDArray.java]
Maybe we should consider if our Tensor can be easily (zero-copy) wrapped by
djl.ai's since they seem to have a similar structure, though it seems they also
have their own memory management model.
> [Java] Implement non-sparse tensors
> -----------------------------------
>
> Key: ARROW-10101
> URL: https://issues.apache.org/jira/browse/ARROW-10101
> Project: Apache Arrow
> Issue Type: Improvement
> Components: Java
> Reporter: David Li
> Assignee: David Li
> Priority: Major
> Labels: pull-request-available
> Time Spent: 20m
> Remaining Estimate: 0h
>
> We'd like to be able to round-trip NumPy ndarrays through Java, and create
> tensors in Java that can be eventually mapped to ndarrays in Python. Having
> even a basic Tensor implementation, with extension types, as a contrib module
> would help greatly.
> Some prior discussions
> *
> [https://lists.apache.org/thread.html/9b142c1709aa37dc35f1ce8db4e1ced94fcc4cdd96cc72b5772b373b%40%3Cdev.arrow.apache.org%3E]
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