* fix post training quantization bug of memory constrained, support the input be different, test=develop

* remove build_once & name_scope (Conv2D)
test=develop

* fix unittest
test=develop

* Conv2DTranspose

* Conv3D & Conv3DTranspose
test=develop

* Pool2D & BatchNorm

* Embedding

* LayerNorm

* GRUUnit & NCE

* PRelu

* BilinearTensorProduct

* GroupNorm & SpectralNorm

* TreeConv
test=develop

* fix LayerNorm in transformer unnittest
test=develop

* disable LayerNorm or BatchNorm in multicard
test=develop

* refine Layer.create_parameter api
test=develop

* refine LayerNorm, remove begin_norm_axis param, add normed shape check
test=develop

* LayerNorm bug fix
test=develop

* fix ci bug for deleting data files, test=develop

* update, test=develop

* update benchmark for int8v2, QAT1, QAT2 accuracy and performance
test=document_fix

* change according to reviews
test=develop test=document_fix

* improve some descriptions and some models
test=develop test=document_fix

* update models benchmark data
test=develop test=document_fix

* update int8v2 and qat2 performance
test=develop test=document_fix

* add ut for comparing FP32 and QAT INT8

* add save qat transformed model python script
test=develop

* updated

* added missing file

* add "with_label"
test=develop

* performance benchmark as unit test
test=develop

* change names of unnecessary thing

* Change CMakeList.txt for model downloading and UT
test=develop

* change names of functions and params for more readable code
test=develop

* Change PADDLE_ENFORCE messages
test=develop

* fix indent problems
test=develop

* indent problems
test=develop

* fix some typos in AMP. test=develop

* delete useless codes. test=develop

* add global value getter setter, test=develop

* fix error messages, test=develop

* support set model_filename and params_filename in post_training_quantization, test=develop

* Support  more ops in post training quantization, and save the output scale in quantized op.
* Update docs in post training quantization and qat 

test=develop

* Fix bug for inserting add_quant_dequant_op to same variable repetitively in add_quant_dequant_pass, test=develop

* add post training quantization, test=develop
* specify the quantizable op type, test=develop

* add custom black varname test=develop

* fix dtype test=develop

* fix num test=develop

* fix ut test=develop

* fix coverage test=develop

* fix blackvar names test=develop

test=develop

* move pool2d to add_quant_dequant_pass, test=develop

* Fix docs of gru_unit and dynamic_gru.

Fix basic_gru in rnn_impl.py.

Add error messages for param_attr setting in layer_norm api.

Add int64 dtype for expand.

test=develop

* Reopen unit-tests of basic_gru/basic_lstm in rnn_impl.py.
test=develop

* Add unit test for layer_norm api.
test=develop

* Remove the deprecated gru doc fix. test=develop

* Fix basic_gru test coverage. test=develop

* Update API.spec. test=develop

* Update API.spec. test=develop

* Fix test_basic_gru coverage test. test=develop

* Update test_basic_gru in test_layers to use fluid.data
test=develop

* Update test_basic_gru for coverage. test=develop

* fix fuse_reduce_op quantization bug test=develop

* close fuse_all_reduce_ops in PaddleSlim, test=develop

* Leave fake quantization around mul

* Replace Fake with Real Quantized Mul

* Gather all scales from fake_quantize_ops

* Enable uint8 in conv_relu tensors

* Disable int8 mul and restore fake mul

* Fix buf for running QAT on VGG16 and 19

* fix next_tokens of controller

* Follow Wangzhen's comment in PR 18970, test=develop

* Review comments, test=develop

* Leave fake quantization around mul

test=develop

* Replace Fake with Real Quantized Mul

test=develop

* Fix bug in quantize placement pass

Nodes in the graph now have checked type instead of node name when they are to be marked for quantization test=develop

* Make PaddleSlim support PyReader.
* Fix unittest of sensitive pruning.
* Add some assert.