<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">Thank you so much Matthew, Pradeep, and everyone else helping with this effort!<div class=""><br class=""></div><div class="">And thanks Matthew for sharing the slides — very informative! I’ve asked Sebastian for the recording but in the meantime I thought I’d ask a couple of questions about the syntax:</div><div class=""><br class=""></div><div class="">* why isn’t there a Subtract operator? It seems that Subtract[A, B] is much more readable than Add[A, Multiply[Literal[-1], B]]?</div><div class="">* is there a prospect for using actual operators and actual literals here? I think that a lot of reticence about Python typing comes from the annotations being so difficult to read. There’s been some great improvements recently with “Optional[Tuple[Union[Float, Int]]]” becoming “tuple[float | int] | None”, and I hope we can leapfrog the awkward phase with this tensor typing stuff. Again, A - B is much more readable again than Subtract[A, B]. And B-2 is much more readable than Add[B, Literal[-2]].</div><div class=""><br class=""></div><div class="">Other than that, love the work, thank you again!</div><div class=""><br class=""></div><div class="">Juan.</div><div class=""><div><br class=""><blockquote type="cite" class=""><div class="">On 11 Jun 2021, at 5:08 am, Matthew Rahtz <<a href="mailto:mrahtz@google.com" class="">mrahtz@google.com</a>> wrote:</div><br class="Apple-interchange-newline"><div class=""><div dir="ltr" class="">Some links I promised to send around:<div class=""><ul class=""><li class=""><a href="https://github.com/deepmind/tensor_annotations" class="">https://github.com/deepmind/tensor_annotations</a> which has a bunch of experimental shape-aware stubs for TensorFlow and JAX using 'semantic' axis labels<br class=""></li><li class=""><a href="https://github.com/pradeep90/pytorch_examples" class="">https://github.com/pradeep90/pytorch_examples</a> ditto for TensorFlow and PyTorch using value-based axis labels<br class=""></li><li class=""><a href="https://arxiv.org/pdf/2102.13254.pdf" class="">https://arxiv.org/pdf/2102.13254.pdf</a> Similar work in TensorFlow for Swift<br class=""></li><li class=""><a href="https://docs.google.com/presentation/d/1kLS-bz1ZmJIFizZExkm8N9jqAj2oOJzTmUaL8INGefc/edit?usp=sharing&resourcekey=0-eFDyGvcEeeHzF62x6Cwl6Q" class="">Slides</a> for our presentation<br class=""></li><li class=""><a href="https://docs.google.com/document/d/1oaG0V2ZE5BRDjd9N-Tr1N0IKGwZQcraIlZ0N8ayqVg8/edit" class="">Tensor typing meeting details</a><br class=""></li></ul><div class="">Thanks again, everyone!</div></div></div><br class=""><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, 9 Jun 2021 at 22:28, Sebastian Berg <<a href="mailto:sebastian@sipsolutions.net" class="">sebastian@sipsolutions.net</a>> wrote:<br class=""></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">On Tue, 2021-06-08 at 11:40 -0700, Stefan van der Walt wrote:<br class="">
> On Tue, Jun 8, 2021, at 03:23, Juan Nunez-Iglesias wrote:<br class="">
> > Hello! Any chance this could be recorded for those of us in useless<br class="">
> > time zones? 😂 <br class="">
> <br class="">
> I added a note to the agenda; we'll ask the speakers and record if<br class="">
> they don't mind.<br class="">
<br class="">
<br class="">
We have made a recording, but I did not plan on making it available<br class="">
publicly. Please contact me directly if you are interested.<br class="">
<br class="">
Cheers,<br class="">
<br class="">
Sebastian<br class="">
<br class="">
<br class="">
> Stéfan<br class="">
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