From 2ae3ad3b3182143423d8252db0261f1ff6a357a6 Mon Sep 17 00:00:00 2001
From: Dhairya Gandhi <dhairya@juliacopmuting.com>
Date: Sun, 6 Oct 2019 04:46:13 +0530
Subject: [PATCH] doc fixes

---
 src/layers/conv.jl | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/src/layers/conv.jl b/src/layers/conv.jl
index d05dfe4d..f02adb41 100644
--- a/src/layers/conv.jl
+++ b/src/layers/conv.jl
@@ -94,7 +94,7 @@ Standard convolutional transpose layer. `size` should be a tuple like `(2, 2)`.
 Data should be stored in WHCN order. In other words, a 100×100 RGB image would
 be a `100×100×3` array, and a batch of 50 would be a `100×100×3×50` array.
 
-Takes the keyword arguments `use_bias`, `pad`, `stride` and `dilation`.
+Takes the keyword arguments `pad`, `stride` and `dilation`.
 """
 struct ConvTranspose{N,M,F,A,V}
   σ::F
@@ -167,7 +167,7 @@ Note that `out` must be an integer multiple of `in`.
 Data should be stored in WHCN order. In other words, a 100×100 RGB image would
 be a `100×100×3` array, and a batch of 50 would be a `100×100×3×50` array.
 
-Takes the keyword arguments `use_bias`, `pad`, `stride` and `dilation`.
+Takes the keyword arguments `pad`, `stride` and `dilation`.
 """
 struct DepthwiseConv{N,M,F,A,V}
   σ::F
@@ -243,7 +243,7 @@ Data should be stored in WHCN order (width, height, # channels, # batches).
 In other words, a 100×100 RGB image would be a `100×100×3×1` array,
 and a batch of 50 would be a `100×100×3×50` array.
 
-Takes the keyword arguments `use_bias`, `pad`, `stride` and `dilation`.
+Takes the keyword arguments `pad`, `stride` and `dilation`.
 """
 struct CrossCor{N,M,F,A,V}
   σ::F