Use AbstractFFTs instead of FFTW.

Author: maleadt

Project.toml

@@ -3,6 +3,7 @@ uuid = "0c68f7d7-f131-5f86-a1c3-88cf8149b2d7"
 version = "1.0.4"
 
 [deps]
+AbstractFFTs = "621f4979-c628-5d54-868e-fcf4e3e8185c"
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
@@ -11,6 +12,7 @@ Serialization = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
+AbstractFFTs = "0.4"
 Adapt = "0.4.1, 1.0"
 julia = "1.0"
 

src/GPUArrays.jl

@@ -12,7 +12,7 @@ using Printf
 using LinearAlgebra.BLAS
 using Base.Cartesian
 
-using FFTW
+using AbstractFFTs
 
 using Adapt
 

src/array.jl

@@ -225,12 +225,12 @@ struct FFTPlan{T}
     p::T
 end
 
-FFTW.plan_fft(A::JLArray; kw_args...) = FFTPlan(plan_fft(A.data; kw_args...))
-FFTW.plan_fft!(A::JLArray; kw_args...) = FFTPlan(plan_fft!(A.data; kw_args...))
-FFTW.plan_bfft!(A::JLArray; kw_args...) = FFTPlan(plan_bfft!(A.data; kw_args...))
-FFTW.plan_bfft(A::JLArray; kw_args...) = FFTPlan(plan_bfft(A.data; kw_args...))
-FFTW.plan_ifft!(A::JLArray; kw_args...) = FFTPlan(plan_ifft!(A.data; kw_args...))
-FFTW.plan_ifft(A::JLArray; kw_args...) = FFTPlan(plan_ifft(A.data; kw_args...))
+AbstractFFTs.plan_fft(A::JLArray; kw_args...) = FFTPlan(plan_fft(A.data; kw_args...))
+AbstractFFTs.plan_fft!(A::JLArray; kw_args...) = FFTPlan(plan_fft!(A.data; kw_args...))
+AbstractFFTs.plan_bfft!(A::JLArray; kw_args...) = FFTPlan(plan_bfft!(A.data; kw_args...))
+AbstractFFTs.plan_bfft(A::JLArray; kw_args...) = FFTPlan(plan_bfft(A.data; kw_args...))
+AbstractFFTs.plan_ifft!(A::JLArray; kw_args...) = FFTPlan(plan_ifft!(A.data; kw_args...))
+AbstractFFTs.plan_ifft(A::JLArray; kw_args...) = FFTPlan(plan_ifft(A.data; kw_args...))
 
 function Base.:(*)(plan::FFTPlan, A::JLArray)
     x = plan.p * A.data