* support ssd in PsCore

* remove log

* remove bz2

* defalut value

* code style

* parse table class

* code style

* add define

* Update paths to Quant models

* Update description

* Add casting initializers for bf16 training

* Changes after review

* Correct test and add comment

* refactor_check_finite_and_scale_npu_kernel

* fix compile

* add alloc_float_status op

* add alloc_float_status op

* add FloatStatus for check_finite_and_unscale

* refine code

* remove unneccessary logic

* refine for fleet

* support ernie trt-int8 for inference

* fix reshape

fix test sync_with_cpp (#32212)

* Support converting the model from fp32 to fp16

* Use the runtime to create the unsupported_fp16_list using in AMP.

* Add more infos about supported ops.

* Add some comments for the function of OpSupportedInfos.

* Fix the unit test of test_multi_precision_fp16_train.

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

* update, test=develop

* 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

* fix entry

* fix distributed lookup table fuse case

* fix entry bug at first time

* move entry from paddle.fluid -> paddle.distributed

* fix ut with paddle.enable_static()
Co-authored-by: Nmalin10 <malin10@baidu.com>

* Use correct master weights in AdamW.

* Just modify the master weight.

* Update for CI Coverage.

post quantize support insert fake_quantize_dequantize node before the OPs that will be used in VIS's faceid models (#30659)

test=develop

* Fix the error of save_quantized_model

* add fleet amp.init()

* add unittest for fleet_amp_init

* Collect weight threshold of lstm, test=develop

* skip quantizing ops in cpu inference, test=develop

* Implemented AddQuantDequantPass in imperative quantization.

* Supported LeakyReLU Quantization

* For meeting coverage rate.

* Changed the file name of test of AddQuantDequant

* Implemented more Quantized NoWeightLayers.

* Fix the loss cannot align problem between static and dynamic model quantization, add swish as supported quantized layer in imperative quantization.

* remove noweight_list

* support 2.0 API such as Pool2D and ReLu