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Release 0.6.0
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@drasmuss drasmuss released this 13 Dec 15:39
· 611 commits to main since this release
v0.6.0
601cf40

Added

  • The SoftLIFRate neuron type now has an amplitude parameter,
    which scales the output in the same way as the new amplitude
    parameter in LIF/LIFRate (see Nengo PR #1325).
  • Added progress_bar=False option to sim.run, which will disable
    the information about the simulation status printed to standard
    output (#17).
  • Added progress bars for the build/simulation process.
  • Added truncated backpropagation option to sim.train (useful for
    reducing memory usage during training). See the documentation for
    details    .

Changed

  • Changed the default tensorboard argument in Simulator from
    False to None
  • Use the new tf.profiler tool to collect profiling data in sim.run_steps and sim.train
    when profile=True.
  • Minor improvements to efficiency of build process.
  • Minor improvements to simulation efficiency targeting small ops
    (tf.reshape/identity/constant).
  • Process inputs are now reseeded for each input when batch processing
    (if seed is not manually set).
  • Users can pass a dict of config options for the profile argument
    in run_steps/train, which will be passed on to the TensorFlow
    profiler; see the tf.profiler documentation for the available
    options    .

Removed

  • Removed backports.print_function dependency

Fixed

  • Fixed a bug where input nodes that were only read as a view were not
    feedable
  • Updated tensorflow-gpu installation check
  • Improved numerical stability of LIFRate gradients (#26)
  • Added more informative error message when data is provided with
    fewer items than sim.minibatch_size (#30)
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