* [PluggableDevice]custom kernel to pten core structs

* mod extension.h for custom op

* compatible python for CI

* support custom context

* refactor to pten

* fix windows and ut

* Add loss conversion from uint16 to float in progressbar class

* Fix test coverage

* Actually fix coverage

* Fix format error

* fix cond grad error when handle tensor array

* add UT

* disable some distribute test case when in CPU test env, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* fix fill_constant bug, *test=kunlun

* fix fill_constant bug,*test=kunlun

* add elementwise_max & unittest

* refine cuda register and unittest

* refine unittest

* refine uinttest for bf16

* refine optest

* refine code

* refine unittest

* refine unittest

* update unittests for activation ops on xpu. test=kunlun

* update input data range. test=kunlun

* update input data range. test=kunlun

* remove infershape and Xshape

* add xshape

* fix bugs when run ci

* fix bugs when run ci

* fix bugs when run infrt test

* pass converage

* update unittest for reduce_prod op on xpu. test=kunlun

* update unittest for reduce_prod op on xpu. test=kunlun

* bugfix: use dtype instead of float32. test=kunlun

* rename pten dir to phi

* rename namespace to phi

* rename infrt pten dir to phi

* resolve conflict

* rename pten to phi in cmake

* revert all infrt change

* change needed files

* fix infrt failed

* fix inference failed

* add more op int16 support

* fix xpu ci

* Enabled test_matmul_v2_op for final state Eager Dygraph

* Fixed minor issue

* Fixed format issue

* remove manual_api

* change sig map of full and empty

* fix fill_any_like_xpu_op

* fix fill_any_like_xpu_op

* fix problem of fill_any_like_xpu_op

* fix conflict

* polish code

* add DistributedFusedLamb op

* polish code

* fix compile error

* compatible with pten changement

* fix rocm compile error

* improve converage

* update upstream/develop

* fix cast_with_ptr.h

* add FLAGS_distributed_lamb_divide_nranks_when_allreduce=1

* fix clip before allreduce

* add use_master_param_norm

* code polish

* fix bug

* fix ROCM ci

* support dtype param for auto_cast

* add amp_dtype for tracer

* add unsupported bf16 list

* support bf16 amp for O2

* refine python interface for bfloat16

* refine code

* refine code

* refine unittest

* refine code

* refine code

* add bf16 o1

* refine code by comment

* add gradient accumulator

* add recompute

* fix_sharding_group

* fix_sharding_group

* new way of unit test , *test=kunlun

* new way of ut, *test=kunlun

* support inplace and intermediate in yaml

* add cmake for dygraph_api

* [MLU]add matmul and matmul_v2 op

* [MLU] fix data_type and del matmul

* [MLU] fix compile error

* [MLU] fix ci_check error

* [MLU]add sync stream ops and broadcast pytest

* [MLU]fix broadcast pytest to add data type

* add softplus op for kunlun2. test=kunlun

* add softplus op for kunlun2. test=kunlun

* fix code style. test=kunlun

* fix code style. test=kunlun

* add more test cases. test=kunlun

* first commit

* teller fix

* bug fix

* enable for pool2d only

* fix global_pooling issue

* pooling_type

* fix test

* update kunlun label_smooth unitest
*test=kunlun

* minor
*test=kunlun

* update inference ut to support nhwc format

* update ut and pass OpCompat

* update ut

* update ut

* Update comment

* [Eager] Support test_imperative_hook_for_layer with _test_eager_guard()

* Polish code name style

* Fix a error name

* Polish code, make it clear and simple

* pten matmul cuda kernel support bf16

* fix pten kernel name

* add matmul_grad bf16 kernel

* add emptylike bf16 kernel

* fix compile

* suppport rocm

* fix error

* fix rocm

* add bf16 header file

* fix compile

* merge legacy to fluid

* Remove legacy code

* Remove legacy code

* Remove DataType test

* Using Tensor directly instead of using EagerTensor

* support gradient_accumulation

* make test_imperative_lod_tensor_to_selected_rows longer

* make test_imperative_lod_tensor_to_selected_rows longer

* refine code

* Rename all EagerTensor to Tensor

* Rename some EagerTensor to Tensor

* rename EagerTensor to EagerVariable

* add more test

* merge develop and refine code