Fix typo

Author: gaurav-arya

docs/src/implementations.md

@@ -33,7 +33,7 @@ To define a new FFT implementation in your own module, you should
 * You can also define similar methods of `plan_rfft` and `plan_brfft` for real-input FFTs.
 
 * We offer an experimental `AdjointStyle` trait to enable automatic computation of adjoint plans via [`Base.adjoint`](@ref),
-(which `AbstractFFTs` uses to implement reverse-mode differentiation rules). To support adjoints in a new plan, define the trait `AbstractFFTs.AdjointStyle(::MyPlan)`. This should return a subtype of `AS <: AbstractFFTs.AdjointStyle` supporting `AbstractFFTs.adjoint_mul(::AdjointPlan, ::AbstractArray, ::AS)`. `AbstractFFTs` pre-implements [`AbstractFFTs.FFTAdjointStyle`](@ref), [`AbstractFFTs.RFFTAdjointStyle`](@ref),
+(which `AbstractFFTs` uses to implement reverse-mode differentiation rules). To support adjoints in a new plan, define the trait `AbstractFFTs.AdjointStyle(::MyPlan)`. This should return a subtype of `AS <: AbstractFFTs.AdjointStyle` supporting `AbstractFFTs.adjoint_mul(::Plan, ::AbstractArray, ::AS)`. `AbstractFFTs` pre-implements [`AbstractFFTs.FFTAdjointStyle`](@ref), [`AbstractFFTs.RFFTAdjointStyle`](@ref),
 [`AbstractFFTs.IRFFTAdjointStyle`](@ref), and [`AbstractFFTs.UnitaryAdjointStyle`](@ref).
 
 The normalization convention for your FFT should be that it computes ``y_k = \sum_j x_j \exp(-2\pi i j k/n)`` for a transform of