From 3695b235ea3cb4d49818663baaddfcdba8645811 Mon Sep 17 00:00:00 2001
From: Avik Pal <avikpal@mit.edu>
Date: Fri, 25 Oct 2024 15:56:34 -0400
Subject: [PATCH] fix: use fast paths for adapt

---
 Project.toml                          |  2 --
 ext/MLDataDevicesChainRulesCoreExt.jl |  3 +--
 src/MLDataDevices.jl                  |  1 -
 src/public.jl                         | 26 +++++---------------------
 test/misc_tests.jl                    | 13 +++++++++++++
 5 files changed, 19 insertions(+), 26 deletions(-)

diff --git a/Project.toml b/Project.toml
index 391724d..7d94339 100644
--- a/Project.toml
+++ b/Project.toml
@@ -7,7 +7,6 @@ version = "1.4.2"
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
 Functors = "d9f16b24-f501-4c13-a1f2-28368ffc5196"
-LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Preferences = "21216c6a-2e73-6563-6e65-726566657250"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 
@@ -54,7 +53,6 @@ Compat = "4.15"
 FillArrays = "1"
 Functors = "0.4.8"
 GPUArrays = "10, 11"
-LinearAlgebra = "1.10"
 MLUtils = "0.4.4"
 Metal = "1"
 Preferences = "1.4"
diff --git a/ext/MLDataDevicesChainRulesCoreExt.jl b/ext/MLDataDevicesChainRulesCoreExt.jl
index 2b8c9c8..e625dc1 100644
--- a/ext/MLDataDevicesChainRulesCoreExt.jl
+++ b/ext/MLDataDevicesChainRulesCoreExt.jl
@@ -8,8 +8,7 @@ using MLDataDevices: AbstractDevice, UnknownDevice, get_device, get_device_type
 @non_differentiable get_device(::Any)
 @non_differentiable get_device_type(::Any)
 
-function ChainRulesCore.rrule(
-        ::typeof(Adapt.adapt_storage), to::AbstractDevice, x::AbstractArray)
+function ChainRulesCore.rrule(::typeof(Adapt.adapt), to::AbstractDevice, x::AbstractArray)
     dev = get_device(x)
     y = Adapt.adapt_storage(to, x)
     if dev === nothing || dev isa UnknownDevice
diff --git a/src/MLDataDevices.jl b/src/MLDataDevices.jl
index c837887..108d8bf 100644
--- a/src/MLDataDevices.jl
+++ b/src/MLDataDevices.jl
@@ -5,7 +5,6 @@ using Functors: Functors, fleaves
 using Preferences: @delete_preferences!, @load_preference, @set_preferences!
 using Random: AbstractRNG, Random
 using Compat: @compat
-using LinearAlgebra: Transpose, Adjoint
 
 abstract type AbstractDevice <: Function end
 abstract type AbstractCPUDevice <: AbstractDevice end
diff --git a/src/public.jl b/src/public.jl
index 6f7c8b8..b6ee2c4 100644
--- a/src/public.jl
+++ b/src/public.jl
@@ -342,29 +342,13 @@ for (dev) in (:CPU, :CUDA, :AMDGPU, :Metal, :oneAPI, :XLA)
     ldev = Symbol(dev, :Device)
     @eval begin
         function (D::$(ldev))(x::AbstractArray{T}) where {T}
-            if isleaf(x)
-                (isbitstype(T) || Internal.special_aos(x)) && return Adapt.adapt(D, x)
-                return map(D, x)
+            if isbitstype(T) || Internal.special_aos(x) || x isa Adapt.WrappedArray
+                return Adapt.adapt(D, x)
             end
-            return Functors.fmap(D, x; exclude=isleaf)
-        end
-        # Fast Paths else we don't get type stability
-        function (D::$(ldev))(x::Transpose{T, <:AbstractArray{T}}) where {T}
-            return transpose(D(parent(x)))
-        end
-        function (D::$(ldev))(x::Adjoint{T, <:AbstractArray{T}}) where {T}
-            return adjoint(D(parent(x)))
-        end
-        function (D::$(ldev))(x::PermutedDimsArray{
-                T, N, perm, iperm, <:AbstractArray{T}}) where {T, N, perm, iperm}
-            y = D(parent(x))
-            return PermutedDimsArray{eltype(y), N, perm, iperm, typeof(y)}(y)
+            return map(D, x)
         end
 
-        function (D::$(ldev))(x::Union{Tuple, NamedTuple})
-            isleaf(x) && map(D, x)
-            return Functors.fmap(D, x; exclude=isleaf)
-        end
+        (D::$(ldev))(x::Union{Tuple, NamedTuple}) = map(D, x)
         function (D::$(ldev))(x)
             isleaf(x) && return Adapt.adapt(D, x)
             return Functors.fmap(D, x; exclude=isleaf)
@@ -418,4 +402,4 @@ If `MLDataDevices.isleaf(x::T)` is not defined, then it will fall back to `Funct
 isleaf(x) = Functors.isleaf(x)
 
 isleaf(::AbstractArray{T}) where {T} = isbitstype(T)
-isleaf(::Union{Transpose, Adjoint, PermutedDimsArray}) = false
+isleaf(::Adapt.WrappedArray) = false
diff --git a/test/misc_tests.jl b/test/misc_tests.jl
index a1023cb..00a9905 100644
--- a/test/misc_tests.jl
+++ b/test/misc_tests.jl
@@ -206,3 +206,16 @@ end
         end
     end
 end
+
+@testset "Zygote.gradient(wrapped arrays)" begin
+    using Zygote
+
+    x = rand(4, 4)
+    cdev = cpu_device()
+
+    @test only(Zygote.gradient(x -> sum(abs2, cdev(x)), x')) isa Matrix{Float64}
+
+    gdev = gpu_device()
+
+    @test only(Zygote.gradient(x -> sum(abs2, gdev(x)), x')) isa Matrix{Float64}
+end