Cleanup for PR submission

Author: borisfom

.travis.yml

@@ -8,7 +8,7 @@ env:
     - WITH_CUDA=true WITH_CMAKE=true WITH_IO=true
     - WITH_CUDA=false WITH_CMAKE=false WITH_IO=false
     - WITH_CUDA=false WITH_CMAKE=true WITH_IO=false PYTHON_VERSION=3
-#  Currently there is no way to install cudnn via apt-get. Uncomment wjen it's available.
+#  Currently there is no way to install cudnn via apt-get. Uncomment when it's available.
 #    - WITH_CUDA=true WITH_CMAKE=false WITH_IO=true WITH_CUDNN=true
 #    - WITH_CUDA=true WITH_CMAKE=true WITH_IO=true WITH_CUDNN=true
 

README.md

@@ -1,7 +1,5 @@
 # Caffe
 
-[![Build Status](https://travis-ci.org/BVLC/caffe.svg?branch=master)](https://travis-ci.org/BVLC/caffe)
-[![License](https://img.shields.io/badge/license-BSD-blue.svg)](LICENSE)
 
 Caffe is a deep learning framework made with expression, speed, and modularity in mind.
 It is developed by the Berkeley Vision and Learning Center ([BVLC](http://bvlc.eecs.berkeley.edu)) and community contributors.

docs/tutorial/layers.md

@@ -39,8 +39,7 @@ In contrast, other layers (with few exceptions) ignore the spatial structure of
     - `n * c_i * h_i * w_i`
 * Output
     - `n * c_o * h_o * w_o`, where `h_o = (h_i + 2 * pad_h - kernel_h) / stride_h + 1` and `w_o` likewise.
-* Sample (as seen in `./models/bvlc_reference_caffenet/train_val.prototxt`)
-
+* Sample (as seen in `./examples/imagenet/imagenet_train_val.prototxt`)
       layer {
         name: "conv1"
         type: "Convolution"

src/caffe/common.cpp

@@ -297,3 +297,4 @@ const char* curandGetErrorString(curandStatus_t error) {
 #endif  // CPU_ONLY
 
 }  // namespace caffe
+