Channel softmax

In this pull request, the behavior of SoftmaxLayer is changed from softmax over `channels*height*width` elements (all elements within a num) to softmax over `channels` elements (all elements at a spatial position within a num). This is for the purpose of running fully-connected layers as convolutions (see Net Surgery: http://nbviewer.ipython.org/github/BVLC/caffe/blob/master/examples/net_surgery.ipynb). It won't damage existing caffe examples, since fully-connected layer top blob has `width==1` and `height==1`.

The CPU version was implemented by @longjon, and I implemented the GPU version, including GPU backward.
Also note that the updated SoftmaxLayer CPU no longer allows in-place computations, since in CPU implementation bottom diff is first changed and then restored
`caffe_mul(top[0]->count(), bottom_diff, top_data, bottom_diff);`
while GPU implementation still allows in-place computations.