* Add progress bar and speed up Quantization Pass

* fix typo

* support fuse conv and bn in QAT (#42255)

* support skip_op_list in PostTrainingQuantization (#42378)

* fix unittest

* add adaround post-quant method

* add some op for full_quantization

* make post training quant API support dataloader

* fix single card 8 unittests in new executor

* fix

* fix

* Support sub graph quant-post

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

* Support converting the model from fp32 to fp16

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

test=develop

* Collect weight threshold of lstm, test=develop

* Remove the cache in post_traning_quantization, test=develop

* Conv2d_transpose and mul support channnelwise quantization, test=develop
* Skip collecting out threshold for output tensor of which the type is not fp32 or fp64, test=develop
* Fix error in test_user_defined_quantization, test=develop
* Add depthwise_conv_bn_fuse, test=develop
* Add conv_transpose_bn_fuse_pass for post_training_quant, test=develop

* Save output threshold by argname_index, test=develop

* Post_training_quantization supports optimize model by fusing, test=develop

* Weight quantization support channel_wise_abs_max method to achieve higher accuracy

* Collect output scale for quantized op and fused op
* Post_training_quantizaion sets batch_generator to support lod tensor

* Post_training_quantizaion supports min_max methon

* post_training_quantization support set bits, test=develop

* up, test=develop

* support weight quantization in post_training_quanzitaion, test=develop
* add test for weight quantization, test=develop

* add mul and matmul quantization, test=develop
* add test for matmul, test=develop

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

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