depwarns

src/data/cmudict.jl

@@ -25,13 +25,13 @@ end
 function phones()
   load()
   Symbol.(first.(split.(split(read(deps("cmudict", "cmudict.phones"),String),
-                        "\n", keep = false), "\t")))
+                        "\n", keepempty = false), "\t")))
 end
 
 function symbols()
   load()
   Symbol.(split(read(deps("cmudict", "cmudict.symbols"),String),
-                "\n", keep = false))
+                "\n", keepempty = false))
 end
 
 function rawdict()
@@ -42,7 +42,7 @@ end
 
 validword(s) = isascii(s) && occursin(r"^[\w\-\.]+$", s)
 
-cmudict() = filter((s, ps) -> validword(s), rawdict())
+cmudict() = filter(p -> validword(p.first), rawdict())
 
 alphabet() = ['A':'Z'..., '0':'9'..., '_', '-', '.']
 

src/onehot.jl

@@ -39,13 +39,13 @@ adapt(T, xs::OneHotMatrix) = OneHotMatrix(xs.height, adapt(T, xs.data))
 end
 
 function onehot(l, labels)
-  i = findfirst(labels, l)
+  i = something(findfirst(isequal(l), labels), 0)
   i > 0 || error("Value $l is not in labels")
   OneHotVector(i, length(labels))
 end
 
 function onehot(l, labels, unk)
-  i = findfirst(labels, l)
+  i = something(findfirst(isequal(l), labels), 0)
   i > 0 || return onehot(unk, labels)
   OneHotVector(i, length(labels))
 end

src/tracker/array.jl

@@ -2,7 +2,7 @@ import Base: *, ==
 
 import LinearAlgebra
 using Statistics
-using LinearAlgebra: Transpose, Adjoint, diagm
+using LinearAlgebra: Transpose, Adjoint, diagm, diag
 
 struct TrackedArray{T,N,A<:AbstractArray{T,N}} <: AbstractArray{T,N}
   tracker::Tracked{A}
@@ -94,7 +94,7 @@ Base.repeat(A::TrackedArray; kw...) = track(repeat, A; kw...)
     S = size(xs)
 
     # Loop through each element of Δ, calculate source dimensions, accumulate into Δ′
-    for (dest_idx, val) in enumerate(IndexCartesian(), data(Δ))
+    for (dest_idx, val) in pairs(IndexCartesian(), data(Δ))
         # First, round dest_idx[dim] to nearest gridpoint defined by inner[dim], then
         # wrap around based on original size S.
         src_idx = [mod1(div(dest_idx[dim] - 1, inner[dim]) + 1, S[dim]) for dim in 1:length(S)]
@@ -256,7 +256,7 @@ LinearAlgebra.vecnorm(x::TrackedArray, p::Real = 2) =
   sum(abs.(x).^p .+ eps(0f0))^(1/p) # avoid d(sqrt(x))/dx == Inf at 0
 
 @grad mean(xs) = mean(data(xs)), Δ -> (Δ / length(xs),)
-@grad mean(xs, region) = mean(data(xs), region), Δ -> (zero(xs) .+ Δ ./ prod(size(xs, region...)),nothing)
+@grad mean(xs, region) = mean(data(xs), dims = region), Δ -> (zero(xs) .+ Δ ./ prod(size(xs, region...)),nothing)
 
 @grad function maximum(xs, r...)
   maximum(data(xs), r...), function (Δ)

src/tracker/back.jl

@@ -96,7 +96,7 @@ end
 
 @forward Grads.grads Base.setindex!, Base.haskey
 
-accum!(g::Grads, x, Δ) = g[x] = haskey(g, x) ? g[x] + Δ : Δ
+accum!(g::Grads, x, Δ) = g[x] = haskey(g, x) ? g[x] .+ Δ : Δ
 
 function back_(g::Grads, c::Call, Δ)
   Δs = c.func(Δ)

test/cuda/cuda.jl

@@ -1,4 +1,4 @@
-using Flux, Flux.Tracker, CuArrays, Base.Test
+using Flux, Flux.Tracker, CuArrays, Test
 using Flux: gpu
 
 info("Testing Flux/GPU")

test/cuda/cudnn.jl

@@ -1,4 +1,4 @@
-using Flux, CuArrays, Base.Test
+using Flux, CuArrays, Test
 
 info("Testing Flux/CUDNN")
 

test/data.jl

@@ -1,5 +1,5 @@
 using Flux.Data
-using Base.Test
+using Test
 
 @test cmudict()["CATASTROPHE"] == :[K,AH0,T,AE1,S,T,R,AH0,F,IY0].args
 

test/layers/stateless.jl

@@ -1,4 +1,4 @@
-using Base.Test
+using Test
 using Flux: onehotbatch, mse, crossentropy, logitcrossentropy,
             σ, binarycrossentropy, logitbinarycrossentropy
 

test/tracker.jl

@@ -1,7 +1,10 @@
 using Flux
-using Flux.Tracker, Base.Test, NNlib
+using Flux.Tracker, Test, NNlib
 using Flux.Tracker: TrackedReal, gradcheck, grad, derivative, checkpoint
 using NNlib: conv
+using Printf: @sprintf
+using LinearAlgebra: diagm, dot, LowerTriangular, norm
+using Statistics: mean
 # using StatsBase
 
 gradtest(f, xs::AbstractArray...) = gradcheck((xs...) -> sum(sin.(f(xs...))), xs...)
@@ -110,7 +113,7 @@ end
     promotiontest(hcat, rand(2,1), rand(2), rand(2,2))
     promotiontest(vcat, rand(3,4,5), rand(1,4,5), rand(2,4,5))
     promotiontest(hcat, rand(4,3,5), rand(4,1,5), rand(4,2,5))
-    promotiontest((x...) -> cat(3, x...), rand(4,5,3), rand(4,5,1), rand(4,5,2))
+    promotiontest((x...) -> cat(x..., dims = 3), rand(4,5,3), rand(4,5,1), rand(4,5,2))
   end
 end
 
@@ -163,7 +166,7 @@ end
 @test gradtest((x, y) -> x .* y, rand(5), rand(5))
 @test gradtest(dot, rand(5), rand(5))
 
-@test gradtest(vecnorm, rand(5))
+@test gradtest(norm, rand(5))
 
 @test gradtest(rand(5)) do x
   y = x.^2

test/utils.jl

@@ -1,5 +1,6 @@
 using Flux: throttle, initn, glorot_uniform, glorot_normal, jacobian
 using StatsBase: std
+using Dates
 
 @testset "Throttle" begin
   @testset "default behaviour" begin