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Make jacobian work with CuArrays #33

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Make jacobian work with CuArrays #33

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36c5256
Make jacobian work with CuArrays
tkf May 27, 2019
aa4e64a
Use broadcasting to construct the Kronecker's delta
tkf May 29, 2019
9c2c05e
Make sure that ȳ's output is a compatible float type
tkf May 30, 2019
f6b0ad4
Use `fill!`/`similar`-based approach to reduce number of indexing
tkf May 30, 2019
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6 changes: 5 additions & 1 deletion src/back.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -173,7 +173,11 @@ Calculate the output jacobian `J = d/dx m(x)` such that each row `i` of `J` corr
"""
function jacobian(f, x::AbstractVector)
y::AbstractVector, back = forward(f, x)
ȳ(i) = [i == j for j = 1:length(y)]
function ȳ(i)
δ = fill!(float(similar(data(y))), false)
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@ChrisRackauckas ChrisRackauckas Aug 27, 2019 •
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δ = false .* y .+ (1:length(y) .== i). Though you should then make it be color_i and loop through colors for it to be sparse, but this is good for now.

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I'll open a fresh PR for this.

δ[i] = true
return δ
end
vcat([transpose(back(ȳ(i))[1]) for i = 1:length(y)]...)
end

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