[arrayfire] 43/61: interop formatting tweaks

[Ghislain Vaillant]

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ghisvail-guest pushed a commit to branch dfsg-clean
in repository arrayfire.

commit 72fe0aee41d23353fb53f879a0bc7bc67e2a26e2
Author: syurkevi <stefan at arrayfire.com>
Date:   Wed Dec 2 14:46:59 2015 -0500

    interop formatting tweaks
---
 docs/pages/interop_cuda.md   | 6 +++---
 docs/pages/interop_opencl.md | 3 ++-
 2 files changed, 5 insertions(+), 4 deletions(-)

diff --git a/docs/pages/interop_cuda.md b/docs/pages/interop_cuda.md
index f2e4e39..5ce92d2 100644
--- a/docs/pages/interop_cuda.md
+++ b/docs/pages/interop_cuda.md
@@ -96,13 +96,13 @@ the appropriate header.
 The first thing these headers allow us to do are to get and set the active device
 using native CUDA device ids. This is achieved through the following functions:
 > **static int getNativeId (int id)** 
-> -- Get the native device id of the CUDA device with id in the ArrayFire context.
+> -- Get the native device id of the CUDA device with **id** in the ArrayFire context.
 
 > **static void setNativeId (int nativeId)**  
-> -- Set the CUDA device with given native id as the active device for ArrayFire.
+> -- Set the CUDA device with given native **id** as the active device for ArrayFire.
 The headers also allow us to retrieve the CUDA stream used internally inside Arrayfire.
 > **static cudaStream_t afcu::getStream(int id)**  
-> -- Get the stream for the CUDA device with id in ArrayFire context.
+> -- Get the stream for the CUDA device with **id** in ArrayFire context.
 These functions are available within the afcu:: namespace and equal C variants 
 can be fund in the full [cuda interop documentation.](\ref cuda_mat.htm)
 
diff --git a/docs/pages/interop_opencl.md b/docs/pages/interop_opencl.md
index 6e270a9..93361d0 100644
--- a/docs/pages/interop_opencl.md
+++ b/docs/pages/interop_opencl.md
@@ -172,7 +172,8 @@ void simple_kernel(__global float *d_y,
 
 Unfortunately, Arrayfire's interoperability functions don't yet allow us to work with
 external OpenCL contexts. This is currently an open issue and can be tracked here:
-https://github.com/arrayfire/arrayfire/issues/1002
+https://github.com/arrayfire/arrayfire/issues/1002.
+
 Once the issue is addressed, it will be possible to take the reverse route and start with
 completely custom OpenCL code, then transfer our results into af::array objects.
 

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