diff --git a/src/cudnn/conv.jl b/src/cudnn/conv.jl
index a4f23c1..6dca751 100644
--- a/src/cudnn/conv.jl
+++ b/src/cudnn/conv.jl
@@ -1,6 +1,6 @@
-
-using NNlib: DenseConvDims
+using NNlib: DenseConvDims, DepthwiseConvDims
 import NNlib: conv!, ∇conv_filter!, ∇conv_data!, conv_bias_act!
+import NNlib: depthwise_conv!, ∇depthwise_conv_filter!, ∇depthwise_conv_data!
 
 using CUDA.CUDNN: scalingParameter, CUDNN_CONVOLUTION, convdims,
                   cudnnConvolutionDescriptor, cudnnConvolutionBwdDataAlgoPerf,
@@ -10,8 +10,8 @@ using CUDA.CUDNN: scalingParameter, CUDNN_CONVOLUTION, convdims,
 
 const CUDNNFloat = Union{Float16,Float32,Float64}
 
-function cudnnConvolutionDescriptor(cdims::DenseConvDims, x::DenseCuArray{T}) where T
-    mode=(NNlib.flipkernel(cdims) ? CUDNN_CROSS_CORRELATION : CUDNN_CONVOLUTION)
+function cudnnConvolutionDescriptor(cdims::ConvDims, x::DenseCuArray{T}) where T
+    mode = (NNlib.flipkernel(cdims) ? CUDNN_CROSS_CORRELATION : CUDNN_CONVOLUTION)
     cudnnConvolutionDescriptor(convdims(nnlibPadding(cdims),size(x),0),
                                convdims(NNlib.stride(cdims),size(x),1),
                                convdims(NNlib.dilation(cdims),size(x),1),
@@ -22,8 +22,8 @@ function cudnnConvolutionDescriptor(cdims::DenseConvDims, x::DenseCuArray{T}) wh
                                Cint(NNlib.groupcount(cdims)))
 end
 
-function conv!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T}, cdims::DenseConvDims;
-               alpha=1, beta=0, algo=-1) where T<:CUDNNFloat
+function conv!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T}, cdims::ConvDims;
+               alpha = 1, beta = 0, algo = -1) where T<:CUDNNFloat
     if cudnnversion() < v"6"
         all(x -> x == 1, dilation(cdims)) || error("Only dilation = 1 is supported in cuDNN version < 6")
     end
@@ -34,9 +34,9 @@ function conv!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T}, cdims
     cudnnConvolutionForward!(y, w, x, d; alpha, beta, z=y)
 end
 
-function conv_bias_act!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T},
-                        cdims::DenseConvDims, bias::DenseCuArray{T}, σ=identity;
-                        z::DenseCuArray{T}=y, alpha=1, beta=0, algo=-1) where T<:CUDNNFloat
+function conv_bias_act!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T}, 
+                        cdims::ConvDims, bias::DenseCuArray{T}, σ = identity;
+                        z::DenseCuArray{T} = y, alpha = 1, beta = 0, algo = -1) where T <: CUDNNFloat
     if cudnnversion() < v"6"
         all(x -> x == 1, dilation(cdims)) || error("Only dilation = 1 is supported in cuDNN version < 6")
     end
@@ -54,7 +54,7 @@ function conv_bias_act!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{
 end
 
 function ∇conv_data!(dx::DenseCuArray{T}, dy::DenseCuArray{T}, w::DenseCuArray{T},
-                     cdims::DenseConvDims; alpha=1, beta=0, algo=-1) where T<:CUDNNFloat
+                     cdims::ConvDims; alpha = 1, beta = 0, algo = -1) where T <: CUDNNFloat
     if cudnnversion() < v"6"
         all(x -> x == 1, dilation(cdims)) || error("Only dilation = 1 is supported in cuDNN version < 6")
     end
@@ -72,7 +72,7 @@ function ∇conv_data!(dx::DenseCuArray{T}, dy::DenseCuArray{T}, w::DenseCuArray
 end
 
 function ∇conv_filter!(dw::DenseCuArray{T}, x::DenseCuArray{T}, dy::DenseCuArray{T},
-                       cdims::DenseConvDims; alpha=1, beta=0, algo=-1) where T<:CUDNNFloat
+                       cdims::ConvDims; alpha = 1, beta = 0, algo = -1) where T <: CUDNNFloat
     if cudnnversion() < v"6"
         all(x -> x == 1, dilation(cdims)) || error("Only dilation = 1 is supported in cuDNN version < 6")
     end
@@ -95,3 +95,18 @@ function ∇conv_bias!(db::DenseCuArray{T}, dy::DenseCuArray{T}; alpha=1, beta=0
     cudnnConvolutionBackwardBias(handle(), alpha, yDesc, dy, beta, bDesc, db)
     return db
 end
+
+function depthwise_conv!(y::DenseCuArray{T}, x::DenseCuArray{T}, w::DenseCuArray{T}, cdims::DepthwiseConvDims;
+               alpha = 1, beta = 0, algo = -1) where T <: CUDNNFloat
+    conv!(y, x, w, cims; alpha, beta, algo)
+end
+
+function ∇depthwise_conv_filter!(dw::DenseCuArray{T}, x::DenseCuArray{T}, dy::DenseCuArray{T},
+                       cdims::ConvDims; alpha = 1, beta = 0, algo = -1) where T <: CUDNNFloat
+  ∇conv_filter!(dw, x, dy, cdims; alpha, beta, algo)
+end
+
+function ∇depthwise_conv_data!(dx::DenseCuArray{T}, dy::DenseCuArray{T}, w::DenseCuArray{T},
+                     cdims::ConvDims; alpha = 1, beta = 0, algo = -1) where T <: CUDNNFloat
+    ∇conv_data!(dx, dy, w, cdims; alpha, beta, algo)
+end