quant aware with infer model

* add rv1109 quant aware training

* quant post hyper param search

* quant post hyper param search
Co-authored-by: Nitminner <397809320@example.com>
Co-authored-by: Nwhs <wanghaoshuang@baidu.com>
Co-authored-by: Nceci3 <ceci3@users.noreply.github.com>

* fix a bug in skip params func

* [Unstructured_prune] add local_sparsity demo

docs：Fix code in doc

* polish distill

* optimize unstructured pruner using GMP

* add uniittests for GMP pruner

* add training scripts for fleet and gmp; add conv1x1 pruning

* add conv1x1 pruning to dygraph

* unify hyper parameters across methods and scripts, static graph

* unify hyper parameters across methods and scripts, dynamic graph

* refine test cases

* fix singlecard training in static graph

* refine readmes

* update unstructured pruner api doc static

* update api docs dygraph

* fix bugs in api docs

* rename UnstructuredPrunerGMP to GMPUnstructuredPruner

* fix some format issues

* remove redundant methods/arguments

* description for gmp configs

* fix minor bugs

* fix test cases accordingly
Co-authored-by: Nwhs <wanghaoshuang@baidu.com>

* Fix an issue in mkldnn doc

* update README.md

* refine distillation

* up

* add test

* fix coverage

* fix unit test error

* update quant docs

* Update quantization_api.rst

* Update quantization_api.rst

* Update quantization_api.rst

* Update qat.py

与之前版本兼容：之前版本直接改动传入的model，所以这里inplace改为true