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1.0 source code.tar.gz (8.5 MB)
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| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| README.md | 2016-01-30 | 3.5 kB | |
| release candidate 3 source code.tar.gz | 2016-01-30 | 7.0 MB | |
| release candidate 3 source code.zip | 2016-01-30 | 7.3 MB | |
| Totals: 3 Items | 14.2 MB | 0 | |
A lot has happened since the last release! This packages up ~800 commits by 119 authors. Thanks all!
With all releases one should do make clean && make superclean to clear out old materials before compiling the new release.
- layers
- batch normalization [#3229] [#3299]
- scale + bias layers [#3591]
- PReLU [#1940] [#2414], ELU [#3388], and log [#2090] non-linearities
- tile layer [#2083], reduction layer [#2089]
- embed layer [#2032]
- spatial pyramid pooling [#2117]
- batch reindex layer [#2966]
- filter layer [#2054]
- solvers: Adam [#2918], RMSProp [#2867], AdaDelta [#2782]
- accumulate gradients to decouple computational and learning batch size [#1977]
- de-duplicate solver code [#2518]
- make solver type a string and split classes [#3166] -- you should update your solver definitions
- MSRA [#1946] and bilinear interpolation [#2213] weight fillers
- N-D blobs [#1970] and convolution [#2049] for higher dimensional data and filters
- tools:
- test caffe command line tool execution [#1926]
- network summarization tool [#3090]
- snapshot on signal / before quit [#2253]
- report ignored layers when loading weights [#3305]
- caffe command fine-tunes from multiple caffemodels [#1456]
- pycaffe:
- python net spec [#2086] [#2813] [#2959]
- handle python exceptions [#2462]
- python layer arguments [#2871]
- python layer weights [#2944]
- snapshot in pycaffe [#3082]
- top + bottom names in pycaffe [#2865]
- python3 compatibility improvements
- matcaffe: totally new interface with examples and tests [#2505]
- cuDNN: switch to v2 [#2038], switch to v3 [#3160], make v4 compatible [#3439]
- separate IO dependencies for configurable build [#2523]
- large model and solverstate serialization through hdf5 [#2836]
- train by multi-GPU data parallelism [#2903] [#2921] [#2924] [#2931] [#2998]
- dismantle layer headers so every layer has its own include [#3315]
- workflow: adopt build versioning [#3311] [#3593], contributing guide [#2837], and badges for build status and license [#3133]
- SoftmaxWithLoss normalization options [#3296]
- dilated convolution [#3487]
- expose Solver Restore() to C++ and Python [#2037]
- set mode once and only once in testing [#2511]
- turn off backprop by skip_propagate_down [#2095]
- flatten layer learns axis [#2082]
- trivial slice and concat [#3014]
- hdf5 data layer: loads integer data [#2978], can shuffle [#2118]
- cross platform adjustments [#3300] [#3320] [#3321] [#3362] [#3361] [#3378]
- speed-ups for GPU solvers [#3519] and CPU im2col [#3536]
- make and cmake build improvements
- and more!
Fixes
- [#2866] fix weight sharing to (1) reduce memory usage and computation (2) correct momentum and other solver computations
- [#2972] fix concat (broken in [#1970])
- [#2964] [#3162] fix MVN layer
- [#2321] fix contrastive loss layer to match Hadsell et al. 2006
- fix deconv backward [#3095] and conv reshape [#3096] (broken in [#2049])
- [#3393] fix in-place reshape and flatten
- [#3152] fix silence layer to not zero bottom on backward
- [#3574] disable cuDNN max pooling (incompatible with in-place)
- make backward compatible with negative LR [#3007]
- [#3332] fix pycaffe
forward_backward_all() - [#1922] fix cross-channel LRN for large channel band
- [#1457] fix shape of C++ feature extraction demo output
Dependencies:
- hdf5 is required
- cuDNN compatibility is now at v3 + v4 and cuDNN v1 and v2 are not supported
- IO dependencies (lmdb, leveldb, opencv) are now optional [#2523]
:coffee:
