* Quantize shape operator

* Add shape op to propagate scales pass

* change fluid.mean to paddle.mean

* reverse some old code examples

* sylwek

prototype params to int8 pass

* trying to make warmup work

* wip

* wip

* change test to cpp test

* review fixes, refactoring

* more refactoring

* add erasevars

* change test to fixture

* rename pass

and reorder erasevars and graphsaferemovenodes

* fix

* more refactoring and fixed bug

* formatting

* remove scale count

* enfroce message too short

* remove erasevars

erasevars couldbe cauuse of memory issues

some other fixes

* add count of successfull fuses to name of new nodes

* FindVar -> GetVar and use ConvResidual pattern

* use tensor->clear() instead of new variable

* Update paddle/fluid/framework/ir/mkldnn/params_quantization_mkldnn_pass_tester.cc
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

* Update paddle/fluid/framework/ir/mkldnn/params_quantization_mkldnn_pass_tester.cc
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

* Update paddle/fluid/inference/tests/api/analyzer_lexical_analysis_gru_tester.cc
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

* add log (review fix)c

* review fix (2 functions to one)

* code review: Conv->QuantizeConv

* revert

* fix formatting

* remove unused functions

* add paddle enforce
Co-authored-by: NTomasz Socha <tomasz.socha@intel.com>

* consolidate conv act passes

* generalize conv_activation

* integrate conv+act tests

* code style format

* whitespaces

* remove timeout from old tests

* implement comments from review

* restore ut

* whitespace

* code style

* transpose

* fixes after review

* method for gettin act

* Change Paddle_enforce error type

* code format

* add missing opcompats

* cmake-lint

* update

* use yapf to format all python file

* yapf exclude two unittests file for they rely on writing and reading file, and format will break them

* disable diff_py_file because too many diff files cause command following failed

* remove attrs from base op

* fix typos

* remove brelu

* undo removing code related to matmul

* remove whitespaces

* undo changes in matmul

* remove empty line

* Add int8 scales gathering pass for convolution

* Fix typo

* Add unittest

* Add corrected unit test

* Change test name

* Remove enabling mkldnn in test

* Speed up test

* Change max examples

* Add functional test

* Change test name

* Add new test case

* Rename pass

* Readd conv_affine_channel fuse pass as mkldnn pass

* Fix formatting

* Add new test to parallel_UT_rule.py

* Fix Coverage and Windows CI issues

* Revert "Fix Coverage and Windows CI issues"

This reverts commit f33459846385c9fd51c07f9f44e7ff283a652637.

* Fix CI errors

* Remove unnecessary conv_eltwise_add_affine_channel fuse pass

* Remove test from parallel_UT_rule.py

* add adaround post-quant method

* refactor eager flags

* fix flags error when we switch from eager to dygraph

* fix ci problem

* fix ci

* fix ci

* merge develop and fix code style

* merge develop and fix code style

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* merge develop

* approve amp for intermediate_dygraph

* add amp_utils for intermediate_dygraph

* add amp needcast check for mlu & npu

* test unittest

* add SetGradNode for set_stop_gradient && add checktensor for GradientHooks

* refine code

* refien unittest of imperative_amp for new dygraph

* inplace api skip amp

* add test_imperative_qat_amp for intermediate amp

* refine code

* refine test_amp ci strategy

* refine unittest code

* refine amp_utils code

* refine amp getpromotetype for some special op

* refine unittest code

* Modify save_quant_model.py to support differnet input and output filenames

* Correct wrong order of arguments

* add some op for full_quantization

* eager, test=develop

* fix bug, test=develop

* eager, test=develop

* merge legacy to fluid

* eager, test=develop

* eager, test=develop

* Refactor TensorAdd func by template and remove gradient_accumulation in eager

* Remove needless target name

* eager, test=develop

* eager, test=develop

* Use overload instead of template

* Remove legacy code

* Remove legacy code

* selectedrows, test=develop

* Remove DataType test

* eager, test=develop

* eager, test=develop

* support gan, test=develop

* Using Tensor directly instead of using EagerTensor

* support gradient_accumulation

* make test_imperative_lod_tensor_to_selected_rows longer

* make test_imperative_lod_tensor_to_selected_rows longer

* refine code

* ptb, test=develop

* Rename all EagerTensor to Tensor

* Rename some EagerTensor to Tensor

* rename EagerTensor to EagerVariable

* eager, test=develop

* eager, test=develop

* eager, test=develop

* eager, test=develop

* add more test

* eager, test=develop

* Support copiable selected rows and merge develop

* save load, eager, test=develop

* save load, eager, test=develop

* refine, test=develop

* remove useless _set_value method

* refine, test=develop

* refine, test=develop

* revert static_runner, test=develop

* EagerTensor to Tensor, test=develop

* refine, test=develop

* refine, test=develop

* clear grad, test=develop

* merge, develop

* merge, develop

* merge, test=develop

* merge, test=develop

* Support quant and part of slice

* support legacy static save

* extend slim tests time

* remove imperative on inference

* remove imperative on inference

* merge develop

* fix typo

* fix typo

* split slice related code into 2 part for imperative and eager

* split slice from inference

* split slice from inference

* fix test_tensor_register_hook
Co-authored-by: NWang Huan <wanghuan29@baidu.com>
Co-authored-by: NWeilong Wu <veyron_wu@163.com>
Co-authored-by: Nwanghuancoder <wanghuancoder@163.com>

* Add mobilenetv3_large performance test

* Disable the BF16 test if the device does not support BF16 computations

* Change test timeout

* remove

* pass

* more pass

* mish unit tests

* code format

* remove unused imports

* code format

* remove hard-coded shape values

* remove timeouts

* remove timeouts v2

* restore timeouts

* rebuild matmul pass: trt and gpu_cpu

* rebuild matmul pass: trt and gpu_cpu

* rebuild matmul pass: trt and gpu_cpu

* rebuild matmul pass: trt and gpu_cpu

* Upadate pass in quant2_int8_mkldnn_pass

* Back to the previous scale_matmul order

* Change place of cpu_quantize_placement_pass