some final changes

Author: ayush1999

src/layers/conv.jl

@@ -1,4 +1,4 @@
-using NNlib: conv, depthwiseconv
+using NNlib: conv, depthwiseconv, crosscor
 
 @generated sub2(::Val{N}) where N = :(Val($(N-2)))
 
@@ -156,11 +156,14 @@ end
 CrossCor(w::AbstractArray{T,N}, b::AbstractVector{T}, σ = identity;
      stride = 1, pad = 0, dilation = 1) where {T,N} =
   CrossCor(σ, w, b, expand.(sub2(Val(N)), (stride, pad, dilation))...)
-CrossCor(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity; init = initn,
-     stride = 1, pad = 0, dilation = 1) where N =
+
+CrossCor(k::NTuple{N,Integer}, ch::Pair{<:Integer,<:Integer}, σ = identity;
+  init = glorot_uniform,  stride = 1, pad = 0, dilation = 1) where N =
   CrossCor(param(init(k..., ch...)), param(zeros(ch[2])), σ,
-       stride = stride, pad = pad, dilation = dilation)
+    stride = stride, pad = pad, dilation = dilation)
+
 @treelike CrossCor
+
 function (c::CrossCor)(x)
   # TODO: breaks gpu broadcast :(
   # ndims(x) == ndims(c.weight)-1 && return squeezebatch(c(reshape(x, size(x)..., 1)))

test/tracker.jl

@@ -186,13 +186,10 @@ end
 @test gradtest(conv, rand(10, 10, 3, 2), randn(Float64,2, 2, 3, 2))
 @test gradtest(conv, rand(10, 10, 10, 3, 2), randn(Float64,2, 2, 2, 3, 2))
 
-<<<<<<< HEAD
 @test gradtest(crosscor, rand(10, 3, 2), randn(Float64,2, 3, 2))
 @test gradtest(crosscor, rand(10, 10, 3, 2), randn(Float64,2, 2, 3, 2))
 @test gradtest(crosscor, rand(10, 10, 10, 3, 2), randn(Float64,2, 2, 2, 3, 2))
-=======
 @test gradtest(depthwiseconv, rand(10,10,3,2), randn(2, 2, 2, 3))
->>>>>>> 30486f9c0394304649bbc6121bd391ef066966c3
 
 @test gradtest(x -> maxpool(x, (2,2)), rand(10, 10, 3, 2))
 @test gradtest(x -> maxpool(x, (2,2,2)), rand(10, 10, 10, 3, 2))