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Enhanced debuggability via freeze() and simplify() APIs.
Enhanced expressiveness with nni.choice, nni.uniform, nni.normal and etc.
Enhanced experience of customization with MutableModule, ModelSpace and ParamterizedModule.
Search space with constraints is now supported.
Improved robustness and stability of strategies.
Supported search space types are now enriched for PolicyBaseRL, ENAS and Proxyless.
Each step of one-shot strategies can be executed alone: model mutation, evaluator mutation and training.
Most multi-trial strategies now supports specifying seed for reproducibility.
Performance of strategies have been verified on a set of benchmarks.
Strategy/engine middleware.
Filtering, replicating, deduplicating or retrying models submitted by any strategy.
Merging or transforming models before executing (e.g., CGO).
Arbitrarily-long chains of middlewares.
New execution engine.
Improved debuggability via SequentialExecutionEngine: trials can run in a single process and breakpoints are effective.
The old execution engine is now decomposed into execution engine and model format.
Enhanced extensibility of execution engines.
NAS profiler and hardware-aware NAS.
New profilers profile a model space, and quickly compute a profiling result for a sampled architecture or a distribution of architectures (FlopsProfiler, NumParamsProfiler and NnMeterProfiler are officially supported).
Assemble profiler with arbitrary strategies, including both multi-trial and one-shot.
Profiler are extensible. Strategies can be assembled with arbitrary customized profilers.
Model Compression
Compression framework is refactored, new framework import path is nni.contrib.compression.
Configure keys are refactored, support more detailed compression configurations. view doc
Support multi compression methods fusion.
Support distillation as a basic compression component.
Support more compression targets, like input, ouptut and any registered paramters.
Support compressing any module type by customizing module settings.
Model compression support in DeepSpeed mode.
Fix example bugs.
Pruning
Pruner interfaces have fine-tuned for easy to use. view doc
Support configuring granularity in pruners. view doc
Support different mask ways, multiply zero or add a large negative value.
Support manully setting dependency group and global group. view doc
A new powerful pruning speedup is released, applicability and robustness have been greatly improved. view doc
The end to end transformer compression tutorial has been updated, achieved more extreme compression performance. view doc
Fix config list in the examples.
Quantization
Support using Evaluator to handle training/inferencing.