rm rules for eachslice, cumsum (FluxML#1253)

* rm rules for eachslice, cumsum

* bump

* bound chainrules

* bump

Project.toml

@@ -1,6 +1,6 @@
 name = "Zygote"
 uuid = "e88e6eb3-aa80-5325-afca-941959d7151f"
-version = "0.6.41"
+version = "0.6.42"
 
 [deps]
 AbstractFFTs = "621f4979-c628-5d54-868e-fcf4e3e8185c"
@@ -25,7 +25,7 @@ ZygoteRules = "700de1a5-db45-46bc-99cf-38207098b444"
 
 [compat]
 AbstractFFTs = "0.5, 1.0"
-ChainRules = "1.35.3"
+ChainRules = "1.36.2"
 ChainRulesCore = "1.9"
 ChainRulesTestUtils = "1"
 DiffRules = "1.4"

src/lib/array.jl

@@ -351,37 +351,6 @@ _backvar(xs, Δ, N::Int, mean) = (convert(eltype(xs), 2/N) .* Δ .* (xs .- mean)
     return s, Δ -> _backvar(xs, Δ ./ (2 .* s), corrected, mean, dims)
 end
 
-@adjoint function cumsum(xs::AbstractVector; dims::Integer = 1)
-  dims == 1 || return copy(xs), Δ -> (Δ,)
-  cumsum(xs), Δ -> (reverse(cumsum(reverse(Δ))),)
-end
-@adjoint function cumsum(xs::AbstractArray; dims::Integer)
-  dims <= ndims(xs) || return copy(xs), Δ -> (Δ,)
-  cumsum(xs; dims=dims), Δ -> begin
-    (reverse(cumsum(reverse(Δ, dims=dims), dims=dims), dims=dims),)
-  end
-end
-
-@adjoint eachrow(x::AbstractVecOrMat) = collect(eachrow(x)), dys -> ∇eachslice(dys, x, 1)
-@adjoint eachcol(x::AbstractVecOrMat) = collect(eachcol(x)), dys -> ∇eachslice(dys, x, 2)
-@adjoint eachslice(x::AbstractArray; dims::Integer) =
-  collect(eachslice(x; dims=dims)), dys -> ∇eachslice(dys, x, dims)
-
-function ∇eachslice(dys, x::AbstractArray, dim::Integer) where {TX}
-  i1 = findfirst(dy -> dy isa AbstractArray, dys)
-  i1 === nothing && return (zero(x),) # all slices get nothing
-  T = promote_type(eltype(dys[i1]), eltype(x))
-  dx = similar(x, T)
-  for i in axes(x, dim)
-    if dys[i] isa AbstractArray
-      copyto!(selectdim(dx,dim,i), dys[i])
-    else
-      selectdim(dx,dim,i) .= 0
-    end
-  end
-  (dx,)
-end
-
 
 # LinearAlgebra
 # =============