From 24d13ac3262e6488227a63e93f971800d2fc756e Mon Sep 17 00:00:00 2001
From: Avik Pal <avikpal@iitk.ac.in>
Date: Tue, 12 Jun 2018 21:32:56 +0530
Subject: [PATCH] Fix missing parenthesis

---
 src/cuda/cudnn.jl | 22 +++++++++++-----------
 1 file changed, 11 insertions(+), 11 deletions(-)

diff --git a/src/cuda/cudnn.jl b/src/cuda/cudnn.jl
index fd0dd7a6..2c2be1d6 100644
--- a/src/cuda/cudnn.jl
+++ b/src/cuda/cudnn.jl
@@ -41,24 +41,24 @@ const BATCHNORM_MIN_EPS = 1e-5
 @inline _wsize(y) = ((1 for _=1:ndims(y)-2)..., size(y)[end-1], 1)
 
 mutable struct bncache
-    mean
-    ivar
+  mean
+  ivar
 end
 
 bncache() = bncache(nothing, nothing)
 
 (CuBN::CuBatchNorm)(x::CuArray{T}; cache = nothing) where T<:Union{Float32, Float64} =
-    CuBN.λ.(cudnnBNForward(CuBN.γ, CuBN.β, x, CuBN.μ, CuBN.σ, CuBN.momentum, cache = cache, eps = CuBN.ϵ, training = CuBN.active))
+  CuBN.λ.(cudnnBNForward(CuBN.γ, CuBN.β, x, CuBN.μ, CuBN.σ, CuBN.momentum, cache = cache, eps = CuBN.ϵ, training = CuBN.active))
 
 function cudnnBNForward(g::CuArray{T}, b::CuArray{T}, x::CuArray{T},
                         running_mean::CuArray{T}, running_var::CuArray{T},
                         momentum::T; cache = nothing,
                         alpha = T(1), beta = T(0),
                         eps = T(1e-5), training = true) where T<:Union{Float32, Float64}
-	y = similar(x)
-	cudnnBNForward!(y, g, b, x, running_mean, running_var, momentum, cache = cache
-		alpha = alpha, beta = beta, eps = eps, training = training)
-	y
+  y = similar(x)
+  cudnnBNForward!(y, g, b, x, running_mean, running_var, momentum, cache = cache,
+                  alpha = alpha, beta = beta, eps = eps, training = training)
+  y
 end
 
 function cudnnBNForward!(y::CuArray{T}, g::CuArray{T}, b::CuArray{T}, x::CuArray{T},
@@ -125,20 +125,20 @@ end
 
 function cudnnBNBackward!(dg::CuArray{T}, g::CuArray{T}, db::CuArray{T},
                          dx::CuArray{T}, x::CuArray{T}, dy::CuArray{T},
-                         running_mean::CuArray{T}, running_var::CuArray{T}
-                         momentum; training = true, 
+                         running_mean::CuArray{T}, running_var::CuArray{T},
+                         momentum; training = true,
                          cache = nothing, eps = T(1e-5),
                          alpha = T(1), beta = T(0),
                          dalpha = T(1), dbeta = T(0)) where T<:Union{Float32, Float64}
     if(training)
-        
+
         if cache !== nothing
             mean, ivar = cache.mean, cache.ivar
             cache_verbose && info("mean and ivar are fetched from the cache")
         else
             mean, ivar = C_NULL, C_NULL
         end
-        
+
         @check ccall((:cudnnBatchNormalizationBackward, libcudnn), cudnnStatus_t,
                      (cudnnHandle_t,cudnnBatchNormMode_t,
                       Ptr{T}, Ptr{T},