Merge pull request #71 from ayush1999/dev_mode

[WIP] mode parameter for Convolution/cross-convolution

Author: MikeInnes

src/conv.jl

@@ -30,6 +30,12 @@ function conv(x::A, w::A; pad = 0, stride = 1, dilation = 1) where A<:AbstractAr
         x, w, pad = pad_, stride = stride_, dilation = dilation)
 end
 
+function crossconv(x::A, w::A; pad = 0, stride = 1, dilation = 1) where A<:AbstractArray
+  pad_, stride_ = padtuple(x, pad), padtuple(x, stride)
+  crossconv!(similar(x, cdims(size(x), dilation_dims(w, dilation), pad_, stride_)),
+        x, w, pad = pad_, stride = stride_, dilation = dilation)
+end
+
 ∇conv_data(dy::A, x::A, w::A; pad = 0, stride = 1, dilation = 1) where A<:AbstractArray =
   ∇conv_data!(zero(x), dy, x, w; pad = pad, stride = stride, dilation = dilation)
 
@@ -39,12 +45,17 @@ end
 # N-D dispatch
 
 function conv!(y::AbstractArray{T,3}, x::AbstractArray{T,3}, w::AbstractArray{T,3};
-               pad = 0, stride = 1, dilation = 1) where T
+               pad = 0, stride = 1, dilation = 1, flipkernel =0) where T
     args = map(x -> reshape(x, size(x,1),1,size(x,2),size(x,3)), (y, x, w))
-    conv!(args..., pad = (pad...,0), stride = (stride...,1), dilation = (dilation...,1))
+    conv!(args..., pad = (pad...,0), stride = (stride...,1), dilation = (dilation...,1), flipkernel=flipkernel)
     return y
 end
 
+function crossconv!(y::AbstractArray, x::AbstractArray, w::AbstractArray;
+               pad = 0, stride = 1, dilation = 1)
+    conv!(y, x, w, pad=pad, stride=stride, dilation=dilation, flipkernel=1)
+end
+
 function ∇conv_filter!(dw::AbstractArray{T,3}, dy::AbstractArray{T,3},
                        x::AbstractArray{T,3}, w::AbstractArray{T,3};
                        pad = 0, stride = 1, dilation = 1) where T
@@ -62,8 +73,8 @@ function ∇conv_data!(dx::AbstractArray{T,3}, dy::AbstractArray{T,3},
 end
 
 conv!(y::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
-      pad = 0, stride = 1, dilation = 1) where T =
-  conv2d!(y, x, w, padding = pad, stride = stride, dilation = dilation)
+      pad = 0, stride = 1, dilation = 1, flipkernel=0) where T =
+  conv2d!(y, x, w, padding = pad, stride = stride, dilation = dilation, mode=flipkernel)
 
 ∇conv_filter!(dw::AbstractArray{T,4}, dy::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
               pad = 0, stride = 1, dilation = 1) where T =
@@ -74,8 +85,8 @@ conv!(y::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
   conv2d_grad_x!(dx, x, w, dy, padding = pad, stride = stride, dilation = dilation)
 
 conv!(y::AbstractArray{T,5}, x::AbstractArray{T,5}, w::AbstractArray{T,5};
-      pad = 0, stride = 1, dilation = 1) where T =
-  conv3d!(y, x, w, padding = pad, stride = stride, dilation = dilation)
+      pad = 0, stride = 1, dilation = 1, flipkernel=0) where T =
+  conv3d!(y, x, w, padding = pad, stride = stride, dilation = dilation, mode=flipkernel)
 
 ∇conv_filter!(dw::AbstractArray{T,5}, dy::AbstractArray{T,5}, x::AbstractArray{T,5}, w::AbstractArray{T,5};
               pad = 0, stride = 1, dilation = 1) where T =
@@ -85,7 +96,7 @@ conv!(y::AbstractArray{T,5}, x::AbstractArray{T,5}, w::AbstractArray{T,5};
             pad = 0, stride = 1, dilation = 1) where T =
   conv3d_grad_x!(dx, x, w, dy, padding = pad, stride = stride, dilation = dilation)
 
-# Depthwise Conv
+  # Depthwise Conv
 
 function dcdims(x::NTuple{4,Int}, w::NTuple{4,Int}, pad, stride)
   ((x[1] + 2 * pad[1] - w[1])÷stride[1] + 1,(x[2] + 2 * pad[2] - w[2])÷stride[2] + 1,w[3]*w[4],x[4])
@@ -96,9 +107,18 @@ function depthwiseconv(x::A, w::A; pad = 0, stride = 1) where A<:AbstractArray
   depthwiseconv!(similar(x, dcdims(size(x), size(w), pad_, stride_)), x, w, pad = pad_, stride = stride_)
 end
 
+function depthwisecrossconv(x::A, w::A; pad = 0, stride = 1) where A<:AbstractArray
+  pad_, stride_ = padtuple(x, pad), padtuple(x, stride)
+  depthwisecrossconv!(similar(x, dcdims(size(x), size(w), pad_, stride_)), x, w, pad = pad_, stride = stride_)
+end
+
 depthwiseconv!(y::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
+      pad = 0, stride = 1, flipkernel=0) where T =
+  depthwiseconv2d!(y, x, w, padding = pad, stride = stride, mode= flipkernel)
+
+depthwisecrossconv!(y::AbstractArray{T,4}, x::AbstractArray{T,4}, w::AbstractArray{T,4};
       pad = 0, stride = 1) where T =
-  depthwiseconv2d!(y, x, w, padding = pad, stride = stride)
+  depthwiseconv!(y, x, w, pad = pad, stride = stride, flipkernel=1)
 
 ∇depthwiseconv_data(dy::A, x::A, w::A; pad = 0, stride = 1) where A<:AbstractArray =
   ∇depthwiseconv_data!(zero(x), dy, x, w; pad = pad, stride = stride)