Great job! Dahua
On Saturday, December 20, 2014 5:54:02 PM UTC+8, Chiyuan Zhang wrote: > > Mocha <https://github.com/pluskid/Mocha.jl> is a Deep Learning framework > for Julia. Two major changes in v0.0.5: > > - CUDA backend now available on Mac > - Mocha now handles general ND-tensors (originally everything was > restricted to 4D tensor), making it much easier to deal with non-vision > data > > Detailed change log: > > - Infrastructure > - *{Breaking Changes}* cuDNN 6.5 R2 (Release Candidate) (@JobJob) > - cuDNN 6.5 R2 is *NOT* backward compatible with 6.5 R1 > - Forward convolution speed up > - Pooling with padding is supported > - Mac OS X is supported > - 4D-tensor -> ND-tensor > - Mocha is now capable of handling general ND-tensor > - Except that (for now) ConvolutionLayer and PoolingLayer still > requires the inputs to be 4D > - The generalization is *almost* backward compatible, except > - The interface for ReshapeLayer changed b/c the target shape > needs to be ND, instead of 4D now > - Parameters added for some layers to allow the user to > specify which dimension to operate on > - The output of InnerProductLayer is now 2D-tensor instead of > 4D > - Unit-tests are expanded to cover test cases for ND-tensor when > applicable > - Interface > - print a constructed Net to get a brief overview of the geometry > of input/output blobs in each layers > - Documentation > - Setup the Roadmap Ticket > <https://github.com/pluskid/Mocha.jl/issues/22>, > duscussions/suggestions are welcome > - Update everything to reflect 4D -> ND tensor changes > - Document for parameter norm constraints > - Developer's Guide for blob and layer API > > Best, > pluskid >
