Adapt lenet_multistep_solver.prototxt to current solvers
Sometimes anaconda is installed in root.

Helps fix #489.
Merge pull request #1293 from sguada/new_lr_policies

Fixed paths for Added Multistep, Poly and Sigmoid learning rate decay policies
Merge pull request #1296 from crizCraig/patch-5

Sometimes anaconda is installed in root.
Fix init current_step
Merge pull request #1308 from sguada/new_lr_policies

[accidental PR: step size fix]
Moved caffe_conv to math_functions.cpp
Added `LoopConvolutionLayer` and its test
You can use LoopConvolutionLayer as engine=LOOP

Note that it works totally the same as ConvolutionLayer unless you use
CPU-mode.
Added simple loop convolution utility

conv_filter for output activation, conv_weight for backprop to weight
and conv_image for backprop to input. These are technically not a
true convolution, they doesn't flip filters.
Added `LoopConvolutionLayer`

LoopConvolutionLayer uses simple convolution implementation, you
can find that in "caffe/util/loop_convolution.hpp".
Added a test for LoopConvolutionLayer
Revert caffe_conv deletion
Now we use loop accumulation for bias diff
Refactoring
Added an example which use LoopConvolutionLayer

This is really slow implementation. In this example, you use
LoopConvolutionLayer instead of ConvolutionLayer, and use run with CPU.
Resolve rebase conflict.
Fixed compiler warnings
Renamed to `NaiveConvolutionLayer`
Rename the names of naive convolution engines