Mike J Innes
Mike J Innes
@spencerlyon2 That's OK, I think Shashi's right that this is going to be happening at the level of Blink (or possibly as part of his exciting WebIO work). @shashi Protobuf...
I've not done any web-y work in ages. But since this issue WebIO is pretty solid and represents the latest thinking on all of this stuff.
Right, exactly. It could be the same type if you modified the display and `getindex` functions to apply the `1/n!` term, so that there's no user-visible change to how TaylorSeries...
I don't think there's any good reason for this beyond us not thinking of it at the time. So please do send a PR!
Yes, it's unfortunate that PR got missed, but since it needs a rebase anyway you may as well just PR against master.
cc @staticfloat When I looked at ImageFiltering.jl, the main issue was that it wasn't designed to support / scale well across large channel dimensions. Not sure if FastConv has the...
Thanks for letting me know, I'll take a look at this.
It's just convolution on a 1D "image"; convolution is well defined for any number of dimensions, and in all cases we require a batch and channel dimension to be provided,...
Wouldn't it be quite a lot easier to reuse CodeMirror and its highlighting in the Jupyter frontend?
Ah, but of course, it is just a trivial definition if you use markdown output; ```julia function Base.show(io::IO, ::MIME"text/markdown", x::Expr) println(io, "```julia") show(io, x) println(io, "```") end ```