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Merged #62 into main.
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Thank you Mark for this excellent RFC, and thank you everyone for your
feedback. This RFC is now merged. I'm really excited to see the results of this
project.
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@manupa-arm can you take a look at Mark's revisions and let us know if this RFC
now looks good to you?
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Thanks for writing this up, Lily, I think standardizing how we handle external
datasets is highly valuable.
To comment on some of the points Tianqi raised, I quite like that this approach
is fundamentally separated from any dependencies as it allows user's to wrap
any dataset or dataloader t
+1 for using `Black` as a global formatter.
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Just wanted to add a +1 to A1 as it seems like the best way to gradually move
TVM towards dynamism without breaking things in the meantime.
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I agree with @masahi, it's not obvious to me that the onnx importer will stop
working and maintaining a new frontend is a lot of ongoing work. +1 to
implementing this on top of TVM rather than inside of it if @ANSHUMAN.TRIPATHY
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Thanks for the discussion and offering to work on implementing this,
@ANSHUMAN.TRIPATHY. Given that Chainer is no longer being developed, it seems
like the ONNX converter should be very stable. Where would new issues be
introduced? Can you give any examples of current problems when importing t
That makes sense, you're right that having it in contrib clears up a lot of my
concerns. Thanks for those clarifications!
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The motivations of this RFC are extremely similar to those in
[pytorch-tvm](https://github.com/pytorch/tvm), however the two implementations
are very different and it is worth discussing the tradeoffs.
- torch-tvm is self contained, it doesn't use any special functions or classes
in TVM. Instea
+1, tons of excellent new features, this is a big step forward for TVM.
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