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https://issues.apache.org/jira/browse/SINGA-333?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16215015#comment-16215015
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Cliff Berg commented on SINGA-333:
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Thanks for this info Wangwei. I will use the Python API. I accept your
assessment that using the Python APIs is easier for a complex network, but it
surprises me. I would have expected that a declarative specification would be
easier to design, examine, and adjust, and it seemed to me that the gRPC
message types were a declarative specification.
I am from an earlier generation of programmers - I started during the 1980s -
and back then there was a strong cultural preference for defining languages. (I
myself was on the team that designed the VHDL language.) The approach would
have been to define a neural network specification language. Indeed, Googling
that, I see that there are some (e.g., EpsiloNN). I have not used any of those,
so I can't comment on them. I suppose that is the intention of ONNX. The
advantages of that approach are that (1) you can analyze designs, using static
analysis tools, (2) you can build a grammar-defined (i.e., standard object
model) AST and optimize a design using an optimization algorithm, (3) you can
explain a design, by explaining its elements in the language syntax or the
standard object model, and (4) the design is statically check-able - you don't
have to run it in order to discover that you are missing an attribute.
I therefore hope that ONNX or something statically analyzable will be
considered.
Very best, - Cliff
> Add support for Open Neural Network Exchange (ONNX) format
> ----------------------------------------------------------
>
> Key: SINGA-333
> URL: https://issues.apache.org/jira/browse/SINGA-333
> Project: Singa
> Issue Type: New Feature
> Reporter: Moaz Reyad
>
> The [Open Neural Network Exchange (ONNX)|https://onnx.ai/] is a format for
> interchanging neural network models between AI systems.
> The ONNX code is available here:
> https://github.com/onnx/onnx
> It can be a useful feature for SINGA to support this format. However, ONNX is
> graph based and some extra work will be required to convert SINGA models to
> this format. May be some core parts of SINGA must to be upgraded first.
> This issue is open for studying and discussing the proposed feature of
> supporting ONNX.
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