* add wide resnet
* update pretrained weights link

* added stack oneDNN FP32 op

* minor change

* CI fix

* added skipping for gpus

* fix for stack op

* CI fix

* CI fix

* Added comment

* CI fix

att, bug fix

* fix rnn grad bug when num_layers is set 2 and dropout_prob is set 0

* add more test for rnn

* refine layer to

* delete comment

* refine logic

* refine code

* refine pure_fp16_init

* refine comment

* delete profiler.cuda_profiler, test=develop

* delete nvprof, test=develop

* add required: gpu, test=develop

* remove cuda_profiler, test=develop

* try to fix CUDA Graph H2D copy bug

* remove useless code

* fix ci

* fix ROCM CI

* fix CUDA_VERSION

* improve CI coverage

* Use cuda virtual memory management and merge blocks, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* window dll, test=develop

* fix cuda error of CUDA_ERROR_NOT_INITIALIZED, test=develop

* use autogrowthv2 for system allocator, test=develop

* remove ~CUDAVirtualMemAllocator(), test=develop

* refine, test=develop

* fix cuda error of CUDA_ERROR_NOT_INITIALIZED, test=develop

* fix cuda error of CUDA_ERROR_NOT_INITIALIZED, test=develop

* fix bug, test=develop

* revert system allocator, test =develop

* revert multiprocessing, test=develop

* fix AutoGrowthBestFitAllocatorV2 mutxt, test=develop

* catch cudaErrorInitializationError when create allocator, test=develop

* fix cuMemSetAccess use, test=develop

* refine cuda api use, test=develop

* refine, test=develop

* for test, test=develop

* for test, test=develop

* switch to v2, test=develop

* refine virtual allocator, test=develop

* Record cuMemCreate and cuMemRelease, test=develop

* refine, test=develop

* avoid out of bounds, test=develop

* rename allocator, test=develop

* refine, test=develop

* use PADDLE_ENFORCE_CUDA_SUCCESS, test=develop

* for test,test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

目前的fused_attention_op不支持attn_mask=None的输入，本PR对此进行了补充，并补充了相应的单测逻辑。

* add scope as membership

* functions complete

* fix bugs: garbage collectior

* deal unknow variable holder

* add

* 1. add unittest for operator_base

* code format

* Update the batch size used in test_resnet50_with_cinn.py.
* Enable more debug info.

* - WIP

- compilation fix

- fix

- fixes

- fix

- fix

- fix again

- fix

- another fix

- another compilation fix

- fix

- fix

- fix

- lint

* - pool2d partially stripped from cache

- pool2d partially stripped of caching

* - compilation fix

* - compilation fix

* - Fix to UT of caching

* - Enabling test_conv3d_mkldnn

* - conv_transpose stripped of cache

* - compilation fix

* - fix

* - fix

* - compilation fix

* - fix

* Reverted disabling caching of conv2d

* - compilation fix

* - ut reverted

* Use a more appropriate `Compile` method in cinn_launch_op.

* Update the VizGraph method of CinnCompiler.

* Add resnet50 model training with CINN.

* fix a quantization bug

Add Static CostModel. Static data is based on op benchmark system

Add FLAGS_allow_cinn_ops & FLAGS_deny_cinn_ops for controlling op types used in training with CINN. (#36842)

* Update UT test_parallel_executor_run_cinn.py.

* Add FLAGS_allow_cinn_ops & FLAGS_deny_cinn_ops & FLAGS_cinn_ops_delim.

* Use the custom StringSplit function and remove the FLAGS_cinn_ops_delim flag.

* Add FlagController test.

* Apply lock to the cache_ only in CinnCompiler.

* Add VizGraph & ReadableKey method for CinnCompiler.

* Update the dot style of VizGraph in CinnCompiler.

* add squeezenet

* Support Py3 type annotations in @to_static

* support type hint for args in func

* support type hint assign

* if annotation and value(Constant) are diffent type, we use value type

* polish type_from_annotation()

* code format

* code format

* remove useless commentary

* fix review
Co-authored-by: NAurelius84 <zhangliujie@baidu.com>

add shufflenetv2
Co-authored-by: Ainavo <ainavo@163.com>
Co-authored-by: Npithygit <pyg20200403@163.com>
Co-authored-by: Ainavo <ainavo@163.com>
Co-authored-by: Npithygit <pyg20200403@163.com>

* added conv + hard_sigmoid fuse pass

* Removed IsOptional() statements

* Reverted removing optional

* add randint like

* rm .cc .cu

* Update unity_build_rule.cmake

* try to make test pass

* use python

* update

* update randint_like

* rename test_randint_like_op -> test_randint_like

* update

* update randint like docs

* update randint like

* update

* update

* add bool

* update randint like test

* update

* update

* Refactor conv2d int8 unit test

* Correct according to review and add int8 check

* AutoParallel Save&Load

* tiny modi

* update func name

* tiny fix

* add NotImplementedError

* fix doc

* update func name

* update func param

* update interface

* add unitest & modi make_data_unshard

* update unittest

* update unittest

* fix unittest

* fix cmakelist

* update unittest

* native commit for triple grad of sigmod

* Updated unittests files

* init functional jacobian api

* Updated trible_test func

* Updated gradient_checker & test_script

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* fix dygraph grad to support high differential

* polish API docstring

* Updated gradient checker and some related files

* fix double grad strip error for high differential

* fix double grad strip error for high differential

* Add Sigmoid triple grad tests

* fix dygraph double grad dtype error when calling for high differential senario

* Updated triple grad teses func

* Use np.random to initialize ddx

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* format python code

* support multi input in triple gradient checker

* Add matmul triple grad kernel

* Updated comments of TODO

* Supported some special tests

* Change code-format to follow CI std

* Updated gradient_checker.py

* Fix conflicts

* Removed unnecessary printing log

* Change code style to follow CI std

* Add Dygraph Triple Grad test
Co-authored-by: Nlevi131 <limaolin01@baidu.com>
Co-authored-by: NJiabin Yang <360788950@qq.com>

* refine vlog of interpretercore

* fix ut

* native commit for triple grad of sigmod

* Updated unittests files

* init functional jacobian api

* Updated trible_test func

* Updated gradient_checker & test_script

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* fix dygraph grad to support high differential

* polish API docstring

* Updated gradient checker and some related files

* fix double grad strip error for high differential

* fix double grad strip error for high differential

* Add Sigmoid triple grad tests

* fix dygraph double grad dtype error when calling for high differential senario

* Updated triple grad teses func

* Use np.random to initialize ddx

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* format python code

* support multi input in triple gradient checker

* Add matmul triple grad kernel

* Updated comments of TODO

* Supported some special tests

* Change code-format to follow CI std

* Updated gradient_checker.py

* Fix conflicts

* Removed unnecessary printing log

* Change code style to follow CI std
Co-authored-by: Nlevi131 <limaolin01@baidu.com>
Co-authored-by: NJiabin Yang <360788950@qq.com>