* Enhance multiclass_nms to support LoD for dygraph mode

* fix some error in multiclass_nms

* update GetLodFromRoisNum to GetNmsLodFromRoisNum

* update matrix nms op to api 2.0

* modify code according to review

* Implement the function of OueScaleForTraining/OutScaleForInference in dygraph

test=develop

* add float64 input to ctc_loss

* modified error message of  warpctc

* update repo and tag of warpctc

* add test for warpctc with float64 input

* modified warpctc.cmake to make sure build always

* resolved sample code bug of warpctc

* add core.ops in warpctc dygraph

* fix a bug of test

* Finished ChannelWiseQuantDequantAbsMaxOp and Passed unittests.

* Finished channel-wise quantize strategy in imperative quantization.

* Added Cuda code of ChannelWiseQuantDequantMaxAbsOP
Add Cuda code of ChannelWiseQuantDequantMaxAbsOp

* Add quant_axis for channel_wise quant.

* fixed a bug in unnitests, which will not trigger axis = 1 case and cannot meet the coverage rate requirement.

* Added some assert infomation and fixed some coding style mistakes.

Update amp_check_finite_and_scale_op and add an updating_loss_scaling op for static graph amp training. (#26240)

* update amp_check_finite_and_scale_op for static_amp.

* use amp_check_finite_and_scale in static graph amp.

* update grads to zero when grads own infinite values(as for amp_checkout_finite_and_scale op).

* add update_loss_scaling op in cpp.

* add update_loss_scaling_op unit test.

* update the doc of the check_finite_and_unscale op

* Update the process of gradients updating skipping if the gradients have infinite values.

* update the way to zero grads.

* update test_update_loss_scaling_op.py

* add log info when find infinite grads.

* add the unit test for UpdateLossScaling Layer.

* enhance collect_op for dygraph, test=develop

* enhance detection ops with lod, test=develop

* support none bbox left in generate_proposals, test=develop

* unfiy MultiLevelRoisNum, test=develop

* update core.ops, test=develop

* add op register for new input & output, test=develop

add collective op for cpu using gloo and paddle.distributed.* apis

* add unique_v2 op

* remove unique_v2 op

* update doc

* api2.0 paddle.nn.Bilinear and paddle.nn.functional.bilinear, test=develop

* api2.0 fix code examples, test=develop

* modify test_bilinear_api, about place,to_tensor , test=develop

* re pass pre-commit, test=develop

* Update common.py

* fix BilinearTensorProduct ci error, test=develop

* add SyncBatchNorm,test=develop

* print user-friendly error message

* adjust error sumary

* add nll loss API, update demo code of the comment

* fix bn & in in dy, test=develop

* update instance_norm,test=develop

* fix bugs,test=develop

* add more case in unittest,test=develop

* fix,test=develop

* fix,test=develop

* add amp_check_finite_and_scale op, test=develop

* add cpu kernel, test=develop

* use bool, test=develop

* follow comments, test=develop

* update name generator, test=develop

* use c++ unique name generator, test=develop

Fix the dygraph mode in matmul, add the support in Linear Op

* expand parameters, test=develop

* support resnet, test=develop

* fix resnet, test=develop

* support duplicable out, test=develop

* support ptb

* fix bugs, test=develop

* support null input, test=develop

* fix bugs, test=develop

* fix batchNorm is_test, test=develop

* refine code, test=develop

* follow comments, test=develop

* follow comments, test=develop

* follow comments, test=develop

* follow comments, test=develop

* use function instead of lambda, test=develop

* follow comments, test=develop

* add op function generator, test=develop

* add unittest, test=develop

* follow comments, test=develop

* fix windows compilation problem, test=develop