* Post_training_quantizaion supports min_max methon

* Added an option to use external FP32 model in QAT comparison test

* Doc update with Ernie QAT INT8 benchmarking

test=develop

* fixes after review

test=develop

* remove ernie part, test=develop test=document_fix

* Fix model name for qatv2

test=develop test=document_fix

* Add Ernie data

test=develop test=document_fix

* update ERNIE benchmark with baidu QA results, test=develop test=document_fix
Co-authored-by: Nbingyanghuang <33643817+bingyanghuang@users.noreply.github.com>
Co-authored-by: NMichał Gallus <sand3r@interia.eu>

* a test for Ernie QAT INT8 accuracy check

test=develop

* Remove NLP comparison test to split PRs

test=develop

* Fix typo and tabs, delete commented lines

test=develop

* re-combine the 2 PRs, test=develop
Co-authored-by: NMichał Gallus <sand3r@interia.eu>
Co-authored-by: Nbingyanghuang <33643817+bingyanghuang@users.noreply.github.com>

* post_training_quantization support set bits, test=develop

* up, test=develop

* support weight quantization in post_training_quanzitaion, test=develop
* add test for weight quantization, test=develop

* add mul and matmul quantization, test=develop
* add test for matmul, test=develop

test=develop

* fix post training quantization bug of memory constrained, support the input be different, test=develop

* fix ci bug for deleting data files, test=develop

* update, test=develop

* update benchmark for int8v2, QAT1, QAT2 accuracy and performance
test=document_fix

* change according to reviews
test=develop test=document_fix

* improve some descriptions and some models
test=develop test=document_fix

* update models benchmark data
test=develop test=document_fix

* update int8v2 and qat2 performance
test=develop test=document_fix

* add ut for comparing FP32 and QAT INT8

* add save qat transformed model python script
test=develop

* updated

* added missing file

* add "with_label"
test=develop

* performance benchmark as unit test
test=develop

* change names of unnecessary thing

* Change CMakeList.txt for model downloading and UT
test=develop

* change names of functions and params for more readable code
test=develop

* Change PADDLE_ENFORCE messages
test=develop

* fix indent problems
test=develop

* indent problems
test=develop

* add global value getter setter, test=develop

* fix error messages, test=develop

* support set model_filename and params_filename in post_training_quantization, test=develop

* Support  more ops in post training quantization, and save the output scale in quantized op.
* Update docs in post training quantization and qat 

* Fix bug for inserting add_quant_dequant_op to same variable repetitively in add_quant_dequant_pass, test=develop

* add post training quantization, test=develop
* specify the quantizable op type, test=develop

* move pool2d to add_quant_dequant_pass, test=develop

* Make PaddleSlim support PyReader.
* Fix unittest of sensitive pruning.
* Add some assert.

* Add support for new QAT models

test=develop
Co-Authored-By: NMichał Gallus <michal.gallus@intel.com>
Co-Authored-By: NWojciech Uss <wojciech.uss@intel.com>

* fixed fps results

test=develop

* fix top5 accuracy drop problem

* updated for new QAT models

* skip quantizing average pooling - dirty but working

* add missing pass

* added missing conv+brelu fuse pass

* removed a call to non-existent pass

test=develop

* renamed pass

test=develop

* Adjust finding pooling scale to newest QAT models

* Remove unnecessary code from quantization_mkldnn_pass

* Copy Pooling input scale to output scale in QAT

* Refactor & remove unused code in QAT

* Incorporate fp32 FC into QAT

test=develop

* Enable graph drawing with debug flag

test=develop

* Add tests for QATv2

* Fix paths for QATv2 models

test=develop

* Add option to save transformed int8 qat model

test=develop

* Remove redundant lines from qat mkldnn pass

test=develop

* Delegate disablement of avg pooling to qat

test=develop

* fix CI bug, test=develop

* Follow Wangzhen's Review, test=develop

* Update API.spec

test=develop

* Name False in (is_unsigned, TensorScale) tuple

test=develop

1. Support customize eval function instead of eval program.
2. Fix loading checkpoint in quantization strategy.
3. Support saving eval model when saving a checkpoint.
4. Fix decoder of loading context in PaddleSlim.
5. Fix restoring from the checkpoint of uniform prune strategy.
6. Support saving eval model and infer model during training.
7. Add ‘unitest’ for saving eval model, saving infer model and uniform pruning restoring from the checkpoint.
8. Fix pruning of depthwise_conv_grad op by updating the groups.