[Fix bug] Init scale node in OutScaleForTrainingPass and enable test_quantization_scale_pass UT (#24393)

* Init scale node in OutScaleForTrainingPass, test=develop
* Enable test_quantization_scale, test=develop

* Enabled quantize all and skip missing in QAT

* QAT: support range-based quantization and scales from attribute

* added support for channelwise

* Collect output scale for quantized op and fused op
* Post_training_quantizaion sets batch_generator to support lod tensor

* 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>

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

test=develop

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

* 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

* support_dispensable_student_loss, test=develop

* add distillation test, test=develop

* fix distillation test non convergence problem, test=develop

* fix test_distillation fail problem, test=develop

test=develop

* Enable MKL-DNN for slim FP32 vs. INT8 tests

test=develop

* added test for MobileNetV1 with MKL-DNN

test=develop

* added unit test for QAT FP32 & INT8 comparison

test=develop

* enabled other models and updated filenames

test=develop

* added accuracy check and multiple batch handling

test=develop

* removed quantization_mkldnn_pass.py

test=develop

* cleanup

test=develop

* updated model paths

test=develop

* renamed tests without MKL-DNN

test=develop

* fix reusing mkldnn pool2d primitive

test=develop

* add performance measuring

test=develop

* fix accuracy statistics

test=develop

* removed non-mkldnn tests

test=develop

* added conv2d_depthwise->conv2d mkldnn transformation

test=develop

* format update

test=develop

* fixed creating key for pool2d grad

test=develop

* added pass

* Fix the accuracy issue while using float precision to get the scale.

test=develop

* Fix the format issue when 'X' is not nchw.

test=develop

* removed output comparing and changed number of images

test=develop

* cmake and comment fix

test=develop

* updated acc threshold for QAT comparison tests

test=develop

* added OMP_NUM_THREADS setting

test=develop

* enable all QAT INT8 tests

test=develop

* restored upstream version of a file

test=develop

* modified directory names

test=develop

* Add auto pruning strategy.
1. Fix compressor.
2. Enhence graph executor.
3. Add SAController
4. Add auto pruning strategy.
5. Add unitest for auto pruning strategy.
test=develop

* Init light-nas

* Add light nas.

* Some fix.
test=develop

* Fix sa controller.
test=develop

* Fix unitest of light nas.
test=develop

* Fix setup.py.in and API.spec.
test=develop

* Fix unitest.
1. Fix unitest on windows.
2. Fix package importing in tests directory.

* 1. Remove unused comments.
2. Expose eval_epoch option.
3. Remove unused function in search_agent.
4. Expose max_client_num to yaml file.
5. Move flops constraint to on_epoch_begin function
test=develop

* Fix light nas strategy.
test=develop

* Make controller server stable.
test=develop

* 1. Add try exception to compressor.
2. Remove unitest of light-nas for windows.
test=develop

* Add comments
Enhence controller
test=develop

* Fix comments.
test=develop

* refactor PR 16865

* delete mergetool files

* test=develop

* test=develop

* test=develop

* test=develop

* create dir for int8 model before call SaveOptimModel

* test=develop

* mkldnn int8 only support linux; test=develop

* refine code; test=develop

* remove comment; test=develop

* refine code; test=develop

* fix bug; test=develop

* add exception for mkldnn_post_training_strategy

* reuse int8v2 CAPI dataset; test=develop

* fix accuracy check bug; test=develop

* remove tab

* convert files to unix format

* test=develop

* reduce CI time;test=develop

* reduce CI time and refine code;test=develop

* refine comment; test=develop

* add cmake FLAGS;test=develop

* remove predict_num;test=develop

test_distillation_strategy always failed on a machine with 4 gpus only, disable temporarily and need to figure out the root cause and add it back later

* Add the calibration tool code for int8 inference and focus test.

* Fix the calibration tool per the review comments.

test=develop

* Update the calibrator doc and remove extra line.

* Fix the invalid is_negative_input attr set on Mobilenet.

* Add the comments and fix the format issue.

test=develop

* Update the CMakelist.txt for Calibration PR.Disable the Calibration UT if not enable MKLDNN.

test=develop

* Update the CMakeList.txt.

test=develop

* Disable the test_calibration case on WIN and MAC.

test=develop

* Add the missing brackets.

test=develop

* Remove the outdated map operator which not supported on Python3.

test=develop

* Fix the style issue.

test=develop

* 1.Update the CMakeList.txt to disable calibration tool ut when the WITH_MKL is not set;
2.Add the workaround to enable the FLAGS_use_mkldnn for PR_CI(PADDLE).

test=develop

* Fix the typo and format the License header.

test=develop

* 1.Add and Update TODOs per review comments.
2.Code clean.

test=develop

* Update label role implementation to use new API

* Try trainable embedding layer

* Fix feed order

* Add infer call

* Update the mnist test cases with the new API syntax.

* Turn on the tests for MNIST

* delete the test files got merged accidently.

* Enable the mnist tests. ready for test driven development.

* Comment out the infer first
This is to confirm that the Trainer.train is working

* Add CMake file to include the tests

* Make the train program only return avg_cost for now

* Update the tests to use the latest syntax

Unify the recognize_digits

* py_test support argument, test_image_classification_train support argument

* use REMOVE_ITEM to rm item from list in cmake