Next: 0.9999

The next release packages up 500+ commits by 17 authors. Thanks all!

* (#404 from @jeffdonahue) the solver configuration can define the net inline; see lenet_consolidated_solver.prototxt.
* (#421, #422 from @sguada) argmax and threshold layers
* (#428 from @shelhamer) make the detection example an R-CNN example
* (#431 from @mavenlin) add support for lmdb storage; this allows multiple reads unlike leveldb.
* (#473 from @shelhamer) Padded max pooling
* (#497 from @jeffdonahue) `propagate_down` in backward method is a vector and is correctly set for each input (fixes long-standing bug in EuclideanLossLayer)
* (#500 from @jeffdonahue) Parameters can be shared between layers / Weight sharing for RNNs, Siamese Nets, etc.
* (#505 from @shelhamer) ConvolutionLayer kernels, padding, and stride can be non-square
* (#518 from @longjon) Compute partial forward / backward passes
* (#531 from @robwhess) AccuracyLayer can compute the top k accuracy
* (#561 from @shelhamer) CPU-only Caffe / "Caffe coldbrew"
* (#614 from @ronghanghu) PoolingLayer kernels, padding, and stride can be non-square
* (#680 from @bhack) SliceLayer to split a blob in two (or more) across channels or samples
* (#740 from @qipeng) Leaky ReLU: non-zero coefficient for negative ReLU inputs
* (#734 from @jeffdonahue) Consolidated network definitions -- train and test nets can now be specified in a single `prototxt`
* (#796 from @jeffdonahue) Print blob statistics during forward/backward passes and updates with SolverParameter setting: `debug_info: true`
* (#800 from @jeffdonahue) Training iterations are 0-indexed
* (#789, #872 from @Yangqing, @shelhamer) Consolidated `caffe` tool for training, finetuning, test, etc. (adds a new dependency on gflags) 
* (#733, #816 from @longjon, @shelhamer) Python interface improvements and bug fix for input preprocessing errors.
* (#825 @shelhamer) introduce caffe-users mailing list

[LICENSE](https://github.com/BVLC/caffe/blob/dev/LICENSE): We have clarified the project license and copyright. While the terms are the same as before, they are now more clear.

DEPENDENCIES / PLATFORM: `lmdb` and `gflags` are now required. Instructions for Ubuntu 14.04 are included. CUDA 6.0 with driver version 340.* or later is recommended -- driver version 331.* cannot be used due to a memory bug in the driver identified by NVIDIA.

DEPRECATION: the new `caffe` tool includes commands for model training and testing, querying devices, and timing models. This tool produces output by default for more informative execution (and no need for `GLOG_logtostderr` environment variable). The corresponding `train_net.bin`, `finetune_net.bin`, `test_net.bin`, `device_query.bin`, and `net_speed_benchmark.bin` are deprecated.