Lock the mex file to avoid Matlab crashes.

Commands like "clear all" and "clear function" causes segmentation faults or errors like these (especially after an 'init'):
 libprotobuf ERROR google/protobuf/descriptor_database.cc:57] File already exists in database: caffe/proto/caffe.proto
 libprotobuf FATAL google/protobuf/descriptor.cc:862] CHECK failed: generated_database_->Add(encoded_file_descriptor, size):
 [libprotobuf ERROR google/protobuf/message.cc:333] Type appears to be in generated pool but wasn't registered: caffe.LayerParameter
 Attempt to restart MATLAB?
To avoid these, lock the the mex file.
Display averaged loss over the last several iterations
fix warning
fix cifar10 paths so they can be run from caffe root
fix types of (Layer)SetUp, Reshape, Forward, and Backward calls

Using the type vector<Blob<Dtype*>* for outputs allows modification of
the vector itself, while it is only okay to modify the blobs pointed to
by the elements of the vector. Switching the types to const
vector<Blob<Dtype>*>& makes them more correct.
Merge pull request #945 from longjon/fixtypes

Fix types of SetUp, Forward, Backward, and gradient checker calls
drop out-of-date conv test comments
optimize 1x1 convolution for Network-in-Network style layers

1x1 convolution with stride 1 is a special case of Caffe matrix
multiplication convolution for which im2col / col2im transformations are
actually the identity. For this special case the memory and
transformation are skipped.
Back-merge
combine col_{data,diff} into single col_buff to halve memory usage

conv forward / backward only need one of the im2col data and diff
at-a-time so consolidating the two saves a lazy allocation.
Merge pull request #1118 from shelhamer/1x1-conv

Optimize 1x1 convolution for Network-in-Network style operation
Back-merge

  define up-to-date all-in-one model for pascal finetuning
  load transform params in window data layer
  include WindowDataLayer in data param upgrade
  Fix typo in LRN-expression in docs
web demo fix, closes #1002
adds a parameter to the LRN layer (denoted as "k" in  [Krizhevsky et al., NIPS 2012])
added support for "k" LRN parameter to upgrade_proto
added matcaffe_demo for the VGG models (RGB input)
added comments to the Matlab demo script
added example usage to the Matlab script
RGB -> BGR in the matlab demo
added a Matlab demo with mean BGR pixel subtraction instead of the mean image subtraction