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Fast, flexible and fun neural networks.

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The full documentation is at


0.5 (2015-12-01)

Changed Behaviour

  • examples now run on CPU by default

  • added and 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.

New Features

  • added a use_conv option to

  • added criterion option to brainstorm.hooks.EarlyStopper hook

  • added function that returns information about the network as a string

  • added 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 and

  • 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

0.5b0 (2015-10-25)

  • First release on PyPI.

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