change specification of forward/backward function and fix layer
definitions appropriately
fix net_speed_benchmark so 'make all' works
make tests compile and pass
test_gradient_check_util: blobid -> blob_id
gradient checker optimization with forward pass loss: only need to run
backward pass to compute analytic gradient (the thing being checked) now
revert unnecessary reordering of lines in softmaxwithlosslayer backward
remove accidentally added empty line
fix softmax loss layer bug; all tests pass
loss in forward pass for concat layer (thought i'd rebased to latest dev
but apparently not)
null pointer defaults for forward loss outputs
post rebase fixes: images layer and padding layer compute loss in
forward
Merge pull request #209 from jeffdonahue/loss-in-forward-pass

Compute loss in the forward pass
loss in forward pass fix for window data layer
Merge pull request #247 from jeffdonahue/loss-in-forward-window-data-layer

Loss in forward pass fix for window data layer
compile caffe without MKL (dependency replaced by boost::random, Eigen3)

- examples, test and pycaffe compile without problem (matcaffe not tested)
- tests show some errors (on cpu gradient tests), to be investigated
- random generators need to be double checked
- mkl commented code needs to be removed
Fixed uniform distribution upper bound to be inclusive
Fixed FlattenLayer Backward_cpu/gpu have no return value
Fix test stochastic pooling stepsize/threshold to be same as max pooling
Fix math funcs, add tests, change Eigen Map to unaligned for lrn_layer

[shelhamer: removed math function tests, since they were merged via
other branches]
relax precision of MultinomialLogisticLossLayer test