- Using cuDNN for a lot of layers now, Fermi is no longer supported
- New transformers added: convert_to_polar_data_transformer, negate_data_transformer
- New readers added: supervised_shuffle_entries_data_reader, image related readers (from raw jpegs stored in a single file)
- Dropout functionality is moved into its own layer with better randomization
- Soft recified linear layer removed
Jan 21, 2015
nnForge v1.1.12
I finally started using cuDNN for some layers of nnForge library, the perf improved. Fermi GPUs are no longer supported; nnForge will run on Kepler and Mawell GPUs only (or CPUs). You will need cuDNN of version at least v2 RC2. Here are all the changes in nnForge v1.1.12:
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