* add option verbose for predict api

* Modified params of some APIs to support tuple and list.

* fixed bug.

solve hccl communicate conflict (#32447)

* add allreduce and broadcast without test (#31024)

add allreduce and broadcast without test

* Refactor HCCLCommContext to be compatible with Paddle (#31359)

Refactor HCCLCommContext to be compatible with Paddle (#31359)

* [NPU] add npu kernel for communication op (#31437)

* add allreduce and broadcast without test

* add c_broadcast_test case

* build c_comm_init and c_create_group operators

* make the whole thing compile

* add broadcast and init op test case but run failed

* make unit test compile

* fix broadcast test bug and change into hcom for ccl

* change c_comm_init and c_create_group ops accordingly

* make tests compile

* transfer code to 27

* compiled successfully in 28, but run failed

* test broadcast in 28, but failed

* make hcom primitives work

* change hccl data type for base.h

* fix broadcast bug

* make attributes work

* fix group name bug

* add allreduce but test failed

* allreduce bug for qiuliang

* allreduce finished

* add allgather and reducescatter

* merge all op code

* add allgather test

* finish run all ccl op test exclude send/recv

* all all op and test exclude send/recv

* send_v2_npu.cc recv_v2_npiu.cc compiled

* fix ccl core dump bug and test allgather, reducescatter, broadcast op

* fix allreduce bug just for test

* hcom send&recv test pass, without hcom_destroy

* for qiuliang test

* Ascend Send&Recv Test Pass

* all op (ex send/recv) ok

* fix bug

* merge all ccl op

* style merge to PaddlePaddle

* merge style

* new merge style

* merge style 2

* insert an empty at the end

* disable ctest for hcom to pass ci
Co-authored-by: Nvoid-main <voidmain1313113@gmail.com>
Co-authored-by: Nf2hkop <f2huestc@outlook.com>

* Add auto-increasing tag id for Hcom OPs (#31702)

* add c_reduce_sum op (#31793)

add c_reduce_sum op

* update Ascendrc hccl to 20.3 (#32126)

update Ascendrc hccl to 20.3 (#32126)

* fix merge code

* change cmake.txt1

* [NPU] Support npu kernel for c sync stream op (#31386)

* sync stream npu op

* add with_ascend_acl

* update c++ unittest

* compile all failed

* try to pre commit

* after pre commit

* merge&compile&test hccl successfully!

* fix code style

* fix code style

* fix bugs about hccl

* fix some bugs

* fix code style

* fix style

* fix style

* fix

* fixed

* merge develop
Co-authored-by: Nlw921014 <liuwei921014@yeah.net>
Co-authored-by: NVoid Main <voidmain1313113@gmail.com>
Co-authored-by: Nf2hkop <f2huestc@outlook.com>
Co-authored-by: Nxiayanming <41795079@qq.com>

* make hapi support amp, and add unittest

* make unittest only support GPU

* update parameters for amp in hapi.Model

* update hapi.Model.prepare interface, and update unittest

* fix test_model.py unittest bug

* add grad clear in dygraph

* use_fp16_guard defaults to True, which could avoid nan

* add input check, and add internal doc link to low level api

* update doc, and decrease the sample num of dataset to avoid timeout

* make hapi amp param  support str 'O1' or 'O2'

* resume calling , modify the code of the check part

* upgrade the usage of Fleet API, and disable 'pure_fp16' param

* fix warning and no grad

* add reducer

* refine envent for memorycopy

* add concat&split for allreduce

* apply concat & split for fuse tensor

* fix nccl dep

* fix the untest, compile problem and ddp initialize problem

* fix untest for mac & add some comments & solve the repeated param in sublayers

* fix untest for windows & fix document

* enhance logger callback for benchmark

* Fix doc format for callbacks, metrics and Model
* Fix code sample and doc

* add early stopping

* add doc for early stopping

* fix sample code bugs

* update infer of mode, update doc, add unittests to increase coverage rate

* fix sample code for early stopping

* update sample code and unittests

* reduce time cost of test_callbacks unittest

* fix model.py code style error

* update hapi save_inference_model output pathname

* update hapi save_inference_model output pathname

* use new 2.0-api paddle.static.io.load_inference_model

* add unittests to increase coverage rate

* add lr scheduler

* return pil image as default according backend

* fix lr scheduler

* fix code style

* update hapi predict interface

* fix code style

* fix docs

* fix docs

* fix docs

* update docs

* fix codes style

* fix unittest

* fix unittest

* fix coverage

* hapi/model step learning rate on batch end. test=develop

* step lr_scheduler on epoch end in hapi/model.py fit. test=develop

* fix model bugs, inputs can be InputSpec instance

* correct error message

* fix dynamic parallel for hapi

* fix code style

* remove input requirment in dygraph Model

* correct unittest

* upadte save inference model in dygraph without input

* fix unittets for test_model.py

* solve conflicts

* solve conflicts

* delete http.log

* fix test_model.py bug, correct initialization of MyModel

* fix unittests bugs

* set paddle manual seed for unittest

* fix Model bugs, because inputs can be list or dict when it is provided.

* add random seed for test_export_deploy_model

* delete redundant codes, because  calls

* Code optimization, error information optimization

* refine vision models

* reproduce summary api

* update model.save_inference_model

* update doc for _save_inference_model, delete useless class in unittests

* make users not be able to set model._inputs be None

* update usage of Model class in unittests

* fix bugs of _verify_spec

* fix bugs of _verify_spec

* add unittest to increase coverage rate

* delete http.log

* update doc for save, remove requirments and limitations for using

* update doc for class Model

Change ProgramTranslator.enable_declarative to ProgramTranslator.enable_to_static to meet API 2.0

* fix conv output_size has no default value bug
* fix summary bug

* add summary for hapi

* replace fluid.optimizer.set_dict with optimizer.set_state_dict

* replace fluid.optimizer.set_dict with optimizer.set_state_dict

* add coverage rate

* Increase coverage rate, fix code style

* Increase coverage rate, fix code style

* add fit to generate optimizer.state_dict() to save .pdopt to increase coverage rate

* delete http.log

* Move hapi form paddle/incubate to paddle

* Remove vision/datasets/utils.py and clean code

* Add sample code for conll05

* Print pull path when saving model

* Fix sample code after paramter_list of SGD is changed to parameters

* Fix bug in wmt16 datase

* fix sample code for hapi.model.save, test=document_fix

* test=document_fix

* update usage of 2.0 API, test=document_fix

* fix bugs, return dygraph back to users while using model.save in dygraph

* fix code style

* add InputSpec

* add unittest for tensorSpec and SimpleNet

* update save_inference_model for hapi

* update save_inference_model to support dygraph

* fix comments

* fix comments

* test=develop

* test, test=develop

* fix dim test, test=develop

* test, test=develop

* add test_export_deploy_model_dynamic

* fix unittest for hapi: save_inference_model

* fix code style

* accept review by guoshengCS

* fix coverage rate

* update doc for save_inference_model and copyright

* change test model back to LeNet() in test_export_deploy_model

* copy jit.save, use LeNet() to test export deploy model

* add return value for dygraph, and fix doc error

* corrected the doc writing

* Delete redundant import and correct import order in sample code.

* remove 'fluid' and add prepare() and fit() in sample code

* correct usage of API 2.0 in sample code

* fix sample code bugs

* fix code style bugs

* fix test_model.py bugs

* set for_inference=True

* correct usage for static.InputSpec

* update doc for model.save

* correct usage of API 2.0

* rename param name for model.save

* correct for_inference as training

* Move paddle/incubate/hapi/metrics to paddle/metric
* Add Precision, Recall and Auc metric

* Rename `Input` into `InputSpec`

* fix argument place of Input api

* Remove paddle.incubate.hapi.loss and reuse the paddle.nn.layer.loss in high level API

* Refine Model

1. Take the network (instance of Layer) as the input of Model.
2. Refine set_dict/load_dict of Layer.
3. Refine Input interface, so update code sample about Input