* 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

* 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

* 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

* clip op extra information when export model,test=ocr

* rename clip_extra parameter to kwargs in save_inference_model, test=ocr

* [RC22] Fix linear with matmul_op replace

* [RC22] Fix linear with matmul_op replace

* [RC22] Fix linear with matmul_op replace

* [RC22] Fix linear with matmul_op replace

* [RC22] Fix linear with matmul_op replace

* Add fusion_lstm INT8 PTQ

* Correct mkldnn_cache_capacity and enable fc_lstm_fuse_pass only for this test

* Change mkldnn_cache_capacity

* PTQ save quantized model

* Wrap simulated layer

* post process the inference model

* refine ptq according comments
* reuse the module to calculate kl threshold

* Save all scales to target ops
* Move quant layers to paddle.nn.quant

* refine the old code

* support moving_average_abs_max and per_channel_abs_max

* Add moving_average_abs_max_scale op

* Convert the test program

* dygraph post training quantization

* refine the ptq config

* refine ptq quantizer

* Combine amp and qat
* add unit test

* del py2 code2

* fix test timeout

* Add wrap for functional api
* Refine the wraped api
* Add unit test for quant functional layers
* Update all unit tests for dygraph qat

* Update paths to Quant models

* Update description

* Support converting the model from fp32 to fp16

* Use layer to calculate output scale
* add backward for moving_average_abs_max_scale and save output scales to op's attr

* Refine saving output scale to infer program

* Fix skip_quant in QAT

* Refine calculating output scale of dygraph qat, test=develop

* Support loading parameters from checkpoint to save quantized model

* Fix the unittest test_moving_average_abs_max_scale_op

* Add unittest of save_quantized_model from checkpoint

* Add comments to explain the function

* Collect weight threshold of lstm, test=develop