History¶

0.5 (2015-12-01)¶

examples now run on CPU by default
added brainstorm.tools.shuffle_data and brainstorm.tools.split to help with data preparation
SigmoidCE and SquaredDifference layers now outputs a loss for each dimension instead of summing over features.
SquaredDifference layer does no longer scale by one half.
Added a SquaredLoss layer that computes half the squared difference and has an interface that is compatible with the SigmoidCE and SigmoidCE layers.
Output probabilities renamed to predictions in SigmoidCE and SigmoidCE layers.

added a use_conv option to brainstorm.tools.create_net_from_spec
added criterion option to brainstorm.hooks.EarlyStopper hook
added brainstorm.tools.get_network_info function that returns information about the network as a string
added brainstorm.tools.extract function that applies a network to some data and saves a set of requested buffers.
brainstorm.layers.mask layer now supports masking individual features
added brainstorm.hooks.StopAfterThresholdReached hook

EarlyStopper now works for any timescale and interval
Recurrent, Lstm, Clockwork, and ClockworkLstm layers now accept inputs of arbitrary shape by implicitly flattening them.
several fixes to make building the docs easier
some performance improvements of NumpyHandler operations binarize_t and index_m_by_v
sped up tests
several improvements to installation scripts

fixed sqrt operation for PyCudaHandler. This should fix problems with BatchNormalization on GPU.
fixed a bug for task_type=’regression’ in brainstorm.tools.get_in_out_layers and brainstorm.tools.create_net_from_spec
removed defunct name argument from input layer
fixed a crash when applying brainstorm.hooks.SaveBestNetwork to rolling_training loss
various minor fixes of the brainstorm.hooks.BokehVisualizer
fixed a problem with sum_t operation in brainstorm.handlers.PyCudaHandler
fixed a blocksize problem in convolutional and pooling operations in brainstorm.handlers.PyCudaHandler