Co-authored-by: Njoanna.wozna.intel <joanna.wozna@intel.com>

* add pure fp16 major function in auto_cast & tracer

* support master weight in dygraph for pure fp16

* check mix dtype of fp16&fp32 for check_finite_and_unscale op

* change pure fp16 funtion name

* refine some bug in auto_cast

* refine auto_cast interface logic

* add param _casted_by_pure_fp16 for class Layer

* support state_dict hook for save model by user appointed dtype in pure_fp16_decorator

* refine pure_fp16_decorator as decorator

* add unittest

* add comment

* add comment

* support recompute

* add comment for auto_cast and decorator

* support to_static_state_dict for paddle.jit.save

* unlimite models num and optimizers num

* add lookup_table in black_list

* fix momentum and layer state_dict

* fix bug in layer state_dict

* fix bug in layer state_dict_helper

* refine unittest

* refine test_momentun_op

* refine interface and some code

* refine amp_decorator interface

* refine pure fp16 interface

* refine master weight interface

* 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

* Small corrections.

* Fix lr for bf16.

* Revert some changes.

* copy found_inf to cpu in advance to improve performance

* add npu test

* add npu test

* refine code

* refine memcpy op

* fix adam

* pass found_inf to adam

* add unittest

* fix bug

* refine unittest

* change unit test's directory

* disable unittest on cpu

* add clear_float_status op

* refine infershape

* fix typo

* refine check_finite_and_scale

* refine code

* cache core.ops, test=develop

* refine, test=develop

* fix undef var

* fix undef var

* PTQ save quantized model

* Wrap simulated layer

* post process the inference model

* opt dygraph python API, test=develop

* Fix unbind bug in manipulation.py

* reduce sum op default fp32, add into amp black list

* reduce_sum default fp32 can avoid return inf when the sum value large than 65504

* 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