Comments (5)
jrevels
commented on August 16, 2024
You're attempting to do ReverseDiff.@forward f(p::Array), which is not supported. Only T<:Real arguments are supported - from the ReverseDiff.@forward docs:
ReverseDiff.@forward(f)(args::Real...)
ReverseDiff.@forward f(args::Real...) = ...
ReverseDiff.@forward f = (args::Real...) -> ...If you remove ReverseDiff.@forward, it should work fine.
There could be a better error message here, and also we should support this in the future.
from reversediff.jl.
domluna
commented on August 16, 2024
Should have mentioned this but even without ReverseDiff.@forward it doesn't work.
ERROR: MethodError: no method matching broadcast_deriv_increment!(::Array{ReverseDiff.TrackedReal{Float64,Float64,Void},2}, ::ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}}, ::Void)
Closest candidates are:
broadcast_deriv_increment!(::AbstractArray{T,N}, ::Any) at /home/dom/.julia/v0.5/ReverseDiff/src/derivatives/elementwise.jl:632
broadcast_deriv_increment!(::Any, ::Any, ::Ref{T}) at /home/dom/.julia/v0.5/ReverseDiff/src/derivatives/elementwise.jl:569
broadcast_deriv_increment!(::AbstractArray{T,N}, ::Any, ::AbstractArray{T,N}) at /home/dom/.julia/v0.5/ReverseDiff/src/derivatives/elementwise.jl:673
...
in special_reverse_exec!(::ReverseDiff.SpecialInstruction{Base.#./,Tuple{ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},Array{ReverseDiff.TrackedReal{Float64,Float64,Void},2}},ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},Tuple{Array{Float64,2},Void}}) at /home/dom/.julia/v0.5/ReverseDiff/src/derivatives/elementwise.jl:465
in reverse_exec!(::ReverseDiff.SpecialInstruction{Base.#./,Tuple{ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},Array{ReverseDiff.TrackedReal{Float64,Float64,Void},2}},ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},Tuple{Array{Float64,2},Void}}) at /home/dom/.julia/v0.5/ReverseDiff/src/tape.jl:74
in (::##5#6)() at /home/dom/.julia/v0.5/ReverseDiff/src/api/tape.jl:80
in seeded_reverse_pass!(::Array{Float64,2}, ::ReverseDiff.TrackedReal{Float64,Float64,Void}, ::ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}}, ::ReverseDiff.Compiled{ReverseDiff.GradientTape{##1#2,ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},ReverseDiff.TrackedReal{Float64,Float64,Void}},##1#2,ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},ReverseDiff.TrackedReal{Float64,Float64,Void},##3#4,##5#6}) at /home/dom/.julia/v0.5/ReverseDiff/src/api/utils.jl:30
in seeded_reverse_pass! at /home/dom/.julia/v0.5/ReverseDiff/src/api/tape.jl:41 [inlined]
in gradient!(::Array{Float64,2}, ::ReverseDiff.Compiled{ReverseDiff.GradientTape{##1#2,ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},ReverseDiff.TrackedReal{Float64,Float64,Void}},##1#2,ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},ReverseDiff.TrackedReal{Float64,Float64,Void},##3#4,##5#6}, ::Array{Float64,2}) at /home/dom/.julia/v0.5/ReverseDiff/src/api/gradients.jl:80
in (::ReverseDiff.##301#302{ReverseDiff.Compiled{ReverseDiff.GradientTape{##1#2,ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},ReverseDiff.TrackedReal{Float64,Float64,Void}},##1#2,ReverseDiff.TrackedArray{Float64,Float64,2,Array{Float64,2},Array{Float64,2}},ReverseDiff.TrackedReal{Float64,Float64,Void},##3#4,##5#6}})(::Array{Float64,2}, ::Array{Float64,2}) at /home/dom/.julia/v0.5/ReverseDiff/src/api/tape.jl:100
Looks like the same error.
from reversediff.jl.
jrevels
commented on August 16, 2024
That looks like what I fixed in #33 - have you updated to the latest release (v0.0.2)? If I copy and paste your code, but remove the @forward, I get:
julia> using ReverseDiff
julia> begin
p = randn(2,3)
f(p) = exp.(p) ./ sum(exp.(p), 2) # softmax
f! = ReverseDiff.compile_gradient(x -> sum(f(x)), similar(p))
f!(similar(p), p)
end
2×3 Array{Float64,2}:
2.77556e-17 5.55112e-17 5.55112e-17
0.0 0.0 0.0from reversediff.jl.
domluna
commented on August 16, 2024
I was on master which is 2 commits ahead it seems. Went to v0.0.2 and it works.
from reversediff.jl.
jrevels
commented on August 16, 2024
Ah, that's not good. Thanks for letting me know. Looks like I should add softmax to the test suite! I'll reopen this.
from reversediff.jl.
Related Issues (20)
- Get a error when calculating the gradient for LSTM
- Error when using scalar vs. vector to operate on tracked inupt HOT 1
- Record `Broadcast.broadcasted` instead of `Broadcast.broadcast`
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- @grad_from_chainrules macro fails when using multi-output functions HOT 2
- ReverseDiff documentation shows issue that has been fixed? Nested differentiation of a closure? HOT 1
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- Enhancement proposal: Modular tape caching HOT 16
- Bug: Derivative of transposed-vector times matrix is incorrect. HOT 5
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- MethodError: vcat(::ReverseDiff.TrackedArray{Float32, Float32, 2, Matrix{Float32}, Matrix{Float32}}, ::Matrix{Float32}) is ambiguous. HOT 4
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from reversediff.jl.