* 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

* fix conv act int8 scale

* add unit test for conv+hard_swish

* make post training quant API support dataloader

* Quantize nearest_interp and nearest_interp_v2

* Check if avx_core supported

* Add depthwise_conv2d to supported quantization list

* add map_matmul passes to quant2_int8_mkldnn_pass

* fix fc+act fuse (activation scale)

* ci fix, c++17 structured bindings not available

* fix ci static check

* reshape+transpose+matmul_v2

* in_name->input_name

* fix pr-ci-static-check

* fix single card 8 unittests in new executor

* fix

* fix

* Support sub graph quant-post

* quantize slice op

* correct test

* fix code formatting

* dequantize matmul and matmul_v2 Y weights in qat2_int8

* review fix

* split conv and mul tests, add matmul test

* fixup

* fix ci build

* remove unused variables

* formatting fix

* remove extra newline at end of file