Add a readme

[mcabbott]

No description provided.

[ToucheSir]

Looks fine to me overall, though others may have thoughts.

[mcabbott]

Maybe it ought to have a "limitations" section? Mentioning that array mutation is unsupported... and that the more your model looks like a simple Flux model the better hope you have? Not sure.

[ToucheSir]

I was under the impression that limited mutation was supported as it is in PyTorch, is that not the case? Either way, IMO a limitations section seems more useful iff. we can come up with some concrete examples of said limitations.

[mcabbott]

Oh I messed up my example. Some do work, via TrackedReal, some don't:

julia> Tracker.gradient([1,2,3]) do x
         y = ones(eltype(x), 2)
         y[1] = x[end]^2
         sum(y)
       end
([0.0, 0.0, 6.0] (tracked),)

julia> Tracker.gradient([1,2,3]) do x  # works under ReverseDiff
         y = fill!(similar(x), 0)
         y[1] = x[end]^2
         sum(y)
       end
ERROR: MethodError: no method matching Float64(::Tracker.TrackedReal{Float64})

 [2] setindex!(A::Vector{Float64}, x::Tracker.TrackedReal{Float64}, i1::Int64)
   @ Base ./array.jl:957

julia> Tracker.gradient([1,2,3]) do x  # fails with ReverseDiff too
         x[1] = x[3]^3
         sum(x)
       end
ERROR: Can't differentiate `setindex!`

[mcabbott]

We can adjust later, maybe this is a start at least...

[coveralls]

Pull Request Test Coverage Report for Build 2900404559

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Details

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• No unchanged relevant lines lost coverage.
• Overall coverage remained the same at 72.141%

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Totals
Change from base Build 2900392751:	0.0%
Covered Lines:	492
Relevant Lines:	682

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