@@ -44,9 +44,10 @@ There are several core features supported by NNI model compression:
.. rubric:: Compression Pipeline
.. image:: ../../img/compression_flow.jpg
:target: ../../img/compression_flow.jpg
.. image:: ../../img/compression_pipeline.png
:target: ../../img/compression_pipeline.png
:alt:
:scale: 20%
The overall compression pipeline in NNI is shown above. For compressing a pretrained model, pruning and quantization can be used alone or in combination.
If users want to apply both, a sequential mode is recommended as common practise.
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@@ -134,9 +135,9 @@ Given the output masks and quantization bits produced by those algorithms, NNI c
The following figure shows how NNI prunes and speeds up your models.
.. image:: ../../img/pipeline_compress.jpg
:target: ../../img/pipeline_compress.jpg
:scale: 40%
.. image:: ../../img/nni_prune_process.png
:target: ../../img/nni_prune_process.png
:scale: 20%
:alt:
The detailed tutorial of Speedup Model with Mask can be found :doc:`here <../tutorials/cp_pruning_speedup>`.
