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NNI v2.6 Release
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@liuzhe-lz liuzhe-lz released this 19 Jan 08:30
· 2 commits to v2.6 since this release
v2.6
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Learn about vigilant mode.

NOTE: NNI v2.6 is the last version that supports Python 3.6. From next release NNI will require Python 3.7+.

Hyper-Parameter Optimization

Experiment

  • The legacy experiment config format is now deprecated. (doc of new config)
    • If you are still using legacy format, nnictl will show equivalent new config on start. Please save it to replace the old one.
  • nnictl now uses nni.experiment.Experiment APIs as backend. The output message of create, resume, and view commands have changed.
  • Added Kubeflow and Frameworkcontroller support to hybrid mode. (doc)
  • The hidden tuner manifest file has been updated. This should be transparent to users, but if you encounter issues like failed to find tuner, please try to remove ~/.config/nni.

Algorithms

  • Random tuner now supports classArgs seed. (doc)
  • TPE tuner is refactored: (doc)
    • Support classArgs seed.
    • Support classArgs tpe_args for expert users to customize algorithm behavior.
    • Parallel optimization has been turned on by default. To turn it off set tpe_args.constant_liar_type to null (or None in Python).
    • parallel_optimize and constant_liar_type has been removed. If you are using them please update your config to use tpe_args.constant_liar_type instead.
  • Grid search tuner now supports all search space types, including uniform, normal, and nested choice. (doc)

Neural Architecture Search

  • Enhancement to serialization utilities (doc) and changes to recommended practice of customizing evaluators. (doc)
  • Support latency constraint on edge device for ProxylessNAS based on nn-Meter. (doc)
  • Trial parameters are showed more friendly in Retiarii experiments.
  • Refactor NAS examples of ProxylessNAS and SPOS.

Model Compression

  • New Pruner Supported in Pruning V2
    • Auto-Compress Pruner (doc)
    • AMC Pruner (doc)
    • Movement Pruning Pruner (doc)
  • Support nni.trace wrapped Optimizer in Pruning V2. In the case of not affecting the user experience as much as possible, trace the input parameters of the optimizer. (doc)
  • Optimize Taylor Pruner, APoZ Activation Pruner, Mean Activation Pruner in V2 memory usage.
  • Add more examples for Pruning V2.
  • Add document for pruning config list. (doc)
  • Parameter masks_file of ModelSpeedup now accepts pathlib.Path object. (Thanks to @dosemeion) (doc)
  • Bug Fix
    • Fix Slim Pruner in V2 not sparsify the BN weight.
    • Fix Simulator Annealing Task Generator generates config ignoring 0 sparsity.

Documentation

  • Supported GitHub feature "Cite this repository".
  • Updated index page of readthedocs.
  • Updated Chinese documentation.
    • From now on NNI only maintains translation for most import docs and ensures they are up to date.
  • Reorganized HPO tuners' doc.

Bugfixes

  • Fixed a bug where numpy array is used as a truth value. (Thanks to @khituras)
  • Fixed a bug in updating search space.
  • Fixed a bug that HPO search space file does not support scientific notation and tab indent.
    • For now NNI does not support mixing scientific notation and YAML features. We are waiting for PyYAML to update.
  • Fixed a bug that causes DARTS 2nd order to crash.
  • Fixed a bug that causes deep copy of mutation primitives (e.g., LayerChoice) to crash.
  • Removed blank at bottom in Web UI overview page.

Contributors

khituras and dosemeion
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