Attempt to make compatible with Julia nightly (#15)

* trying to fix the error that's come up on julia nightly

* CI wasn't triggered

* removed Manifest

* moved CI to 1.7

* bumped up version entry

* revert to 1.3

* drop 1.3 CI

Co-authored-by: Michael Abbott <[email protected]>

Author: pat-alt

.github/workflows/ci.yaml

@@ -16,7 +16,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.3'
+          - '1.6'  # LTS 
           - '1' # Leave this line unchanged. '1' will automatically expand to the latest stable 1.x release of Julia.
           - 'nightly'
         os:

.gitignore

@@ -0,0 +1 @@
+Manifest.toml

Project.toml

@@ -1,7 +1,7 @@
 name = "SliceMap"
 uuid = "82cb661a-3f19-5665-9e27-df437c7e54c8"
 authors = ["Michael Abbott"]
-version = "0.2.6"
+version = "0.2.7"
 
 [deps]
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"

README.md

@@ -28,3 +28,5 @@ how `slicemap(f, A; dims)` works). Similar gradients are also available in
 and in [LazyStack](https://github.com/mcabbott/LazyStack.jl).
 
 There are more details & examples at [docs/intro.md](docs/intro.md). 
+
+

src/SliceMap.jl

@@ -185,11 +185,10 @@ end
 #= JuliennedArrays =#
 
 @adjoint JuliennedArrays.Slices(whole, along...) =
-    Slices(whole, along...), Δ -> (Align(Δ, along...), map(_->nothing, along)...)
+    JuliennedArrays.Slices(whole, along...), Δ -> (Align(Δ, along...), map(_->nothing, along)...)
 
 @adjoint JuliennedArrays.Align(whole, along...) =
-    Align(whole, along...), Δ -> (Slices(Δ, along...), map(_->nothing, along)...)
-
+    Align(whole, along...), Δ -> (JuliennedArrays.Slices(Δ, along...), map(_->nothing, along)...)
 #= Base =#
 
 @adjoint Base.reduce(::typeof(hcat), V::AbstractVector{<:AbstractVector}) =

test/runtests.jl

@@ -35,7 +35,7 @@ Zygote.refresh()
     @test grad ≈ Zygote.gradient(m -> sum(sin, tmapcols(fun, m)), mat)[1]
     @test grad ≈ Zygote.gradient(m -> sum(sin, ThreadMapCols{3}(fun, m)), mat)[1]
 
-    jcols(f,m) = Align(map(f, Slices(m, True(), False())), True(), False())
+    jcols(f,m) = Align(map(f, JuliennedArrays.Slices(m, True(), False())), True(), False())
     @test res ≈ jcols(fun, mat)
     @test grad ≈ Zygote.gradient(m -> sum(sin, jcols(fun, m)), mat)[1]
 
@@ -111,7 +111,7 @@ end
     @test grad ≈ Tracker.gradient(m -> sum(sin, maprows(fun, m)), mat)[1]
     @test grad ≈ Zygote.gradient(m -> sum(sin, maprows(fun, m)), mat)[1]
 
-    jrows(f,m) = Align(map(f, Slices(m, False(), True())), False(), True())
+    jrows(f,m) = Align(map(f, JuliennedArrays.Slices(m, False(), True())), False(), True())
     @test res ≈ jrows(fun, mat)
     @test grad ≈ Zygote.gradient(m -> sum(sin, jrows(fun, m)), mat)[1]
 
@@ -128,12 +128,12 @@ end
     @test grad ≈ Zygote.gradient(x -> sum(sin, slicemap(fun, x, dims=3)), ten)[1]
 
     jthree(f,m) = Align(map(f,
-        Slices(m, False(), False(), True(), False())
+        JuliennedArrays.Slices(m, False(), False(), True(), False())
         ), False(), False(), True(), False())
     @test res ≈ jthree(fun, ten)
     @test grad ≈ Zygote.gradient(m -> sum(sin, jthree(fun, m)), ten)[1]
 
-    j3(f,m) = Align(map(f, Slices(m, 3)), 3)
+    j3(f,m) = Align(map(f, JuliennedArrays.Slices(m, 3)), 3)
     @test res ≈ j3(fun, ten)
     @test grad ≈ Zygote.gradient(m -> sum(sin, j3(fun, m)), ten)[1]