* add gc for multi jobs

* fix job.h

* update OpInfo to OpInOutInfo

* update get_skip_gc_vars algo order

* add int_with_ll to conv

* fix bugs when output_size is specified for conv2d_transpose

* add fetch kernel

* support fetch var in new ir

* fix bug

* polish code

* change array equal to np.testing

* support feed in new ir

* fix bug

* try to hack combine op

* add scope guard

* revert atan2 op

* polish code

* fix vector type bug

* modify feed data type

* demo1

* add test cases

* modify the usage of StepDecay

* refine

* replace PiecewiseDecay(LearningRateDecay) with PiecewiseDecay(LRScheduler)

* fix bug

* fix bug

* replace the StepDecay,MultiStepDecay,LambdaDecay with 2.0 version

* add pos_weight in kernel

* fix unittest

* fix xpu

* fix bce unittest, change infermeta order

* [ROCM] fix cupti, hipcub

* update

* update

* test=cinnunit

* test=cinnunit

* sync to develop of cinn

* test=cinnunit

* test=cinnunit

* [kunlun] fix the dataloader problem in RDMA env

When running multi-machine training with Paddle DataLoader, an
unexpected segmentfault will be raised in DataLoader Process,
where the traceback goes all back to a runtime error that dataloader
workers exit unexpectedly. Similar problems have been discussed
that lead to a misbehavior of OpenCV working in multiprocessing
environment.
See
https://stackoverflow.com/questions/54013846/pytorch-dataloader-stucked-if-using-opencv-resize-method

* code style

* fix 'RuntimeError: context has already been set'

* Update dataloader_iter.py

spawn method raise error 'Can't pickle local object' in some situations

* code format check

* code style

* complement ir type

* fix ir_printer

* [XPU] fix compile issue for XPTI

* bugfix

* bugfix

* add einsum layer

* Enhance the shape check of trt_embedding_eltwise_layernorm_fuse_pass, embedding_eltwise_layernorm_fuse_pass

* block bf16 tests on ROCM

* block more bf16 tests on ROCM

* some unittest cases doesn't have kernels on ROCm

* some unittest cases doesn't have kernels on ROCm

* fix code style

* delete swish_raw

* fix

* Update activation_kernel.cc

* fix

* modify eular_beam

* modify matmul infermeta

* add test

* modify timeout

* base rule

* add sharidng merge

* add sharidng axis merge

* define unified data class for inferencing dist_attr

* test wrap DistTensorSpec in dygraph mode

* matmul main logic done

* define unified data class for inferencing dist_attr

---------
Co-authored-by: NYichen Zhang <zhangyichen03@baidu.com>

* remove the CosineDecay in fluid

* Update test_basic_api_transformation.py

* remove the NaturalExpDecay in fluid

* fix bug

* remove the ExponentialDecay in fluid

* remove the InverseTimeDecay in fluid

* remove the InverseTimeDecay class

* fix bug

* add all_to_all phi operator, kernel, api

* add all_to_all ut

* tinyfix

* feat(cmake): add cmake of cinn

* feat(cmake): add cmake of cinn python test

* feat(cmake): add jit

* feat(cmake): test/CMakeList.txt

* feat(cmake): rebase to develop

* feat(cmake): remove some flags

* fix(cmake): fix cinn's gflags depends

* feat(cmake): add ci scripts of cinn

* feat(cmake): copy code of cinn

* fix(cmake): fix cinn third_party model path

* gflags dynamic dependce

* fix ci build_demo

* tmp update to c++17 of cinn-only test

* fix cinn only with c++17

* add kernel dialect

* change DenseTensorTypeStorage to DenseTensorType

* add test case`

* add first pd_op to kernel dialect

* lower pd op to kernel dialect

* update

* update

* remove useless code

* add attrite print test

* fix bug

* update

* update

* update

* update

* polish code

* fix bug

* polish  code  and add python test

* add test

* fix test error

* add env flag

* fix bug

* revert test env

* change cc_test_old to cc_test

* fix build_static bug

* fix type test error

* udpate cmake

* disable test in windows

* update

* update

* fix bug

* split file

* fix conflict

* polish code and fix conflict

* support place transformer

* finish bug

* add gpu flags

* fix with cuda macro

* update

* add scope guard

* polish code