Co-authored-by: NWangXi <wangxi16@baidu.com>

Co-authored-by: NWangXi <wangxi16@baidu.com>

[cherry-pick][Hybrid Performance] Move the cast op of AMP which cast fp32 param to fp16 param to the optimizer (#34965) (#35296)
Co-authored-by: NWangXi <wangxi16@baidu.com>

Co-authored-by: NWangXi <wangxi16@baidu.com>

* support class center sample of PartialFC

* unitest_quant_dequant

* fix

* fix

* deleted: test_trt_quant_conv2d_dequant_fuse_pass.py

* fix

* polish unittest.

* polish code

* polish code

* [bug fix] fix unfold negative_size_param

* dygraph support more ctc grad scale

* scale for 1.x

* fix unitest

* fix unitest

* format code

* fix unittest

* fix log info

* unittest cov

* fix format;notest,test=cpu,coverage

* skip ctc_loss egs;test=cpu

* warpctc grad cov;test=coverage

* add dygraph test;test=coverage

* format;test=cpu,coverage

* format;test=cpu

* add api compat;test=cpu

* add cpu test

* rename

* rename

* fix

* fix test

* format

* eigen cpu

* eigen gpu grad pass

* cuda gpu pass

* format

* fix ci

* add inplace passes and tests

* update

* fix use_cuda undefined
fix compile error of op compat

* add more ut

* fix CPU CI error

* check adam unique

* fix mac/windows ci, improve coverage

* fix ci error

* follow weihang's comment

* fix BlockDesc::MoveFrom

* follow qiuliang's comment

* update

* follow huihuang's comments

* fix drop_last not work in IterableDataset. test=develop

* Fix typos in english docs for diag and diagflat.

* [NPU] Support npu op:(1)arg_min (2)arg_max

* Modify and add unit test cases

* Modify unit test cases

* add size npu op

* modify support data type

* no longer use NPU size OP

* remove useless comments, add test case

* fix copyright, remove useless include

* Add NPU kernel for nearest_interp op

* Add grad op

* Modify codes according to the review comments

* Modify codes according to the review comments

* add unique_consecutive_op

* add unique_consecutive_op

* add unique_consecutive_op

* add unique_consecutive_op

* add unique_consecutive_op

* add unique_consecutive_op

* add unique_consecutive_op

* add unique_consecutive_op

* remove unity build

* add unique_consecutive op

* add unique_consecutive op

* add enable static

* add noqa

* add space line

* add default case.

* add comma

* add space line

* modify unique_consecutive unittest

* optimize ut coverage

* rebase develop

* improve coverage

* update en docs

* update en docs

* update en docs

* update en docs

* update en docs

* update en doc

* dygraph amp support param_group

* remove unused code

* fix doc

* support margin loss (arcface, cosface, sphereface)

* Support NPU OP hard_swish and hard_swish_grad

* Support NPU OP hard_swish and hard_swish_grad

* add the unittest to compare the result between npu ans cpu

* format the prompt of exception

* replace Min and Max op by ClipByValue op

* fix the precision problem for fp16

* Using HardtanhGrad to improve performace

* fix dice_loss bug

* add p_norm_op_npu

* remove p_norm_grad op

* update

* OP dot: refactor CPU kernels and get better loop performance.

* Minor fix on code format.

* Fixed minor errors.

* Add new API: einsum

* Update the Einsum unit test.

One case failed with matmul_v2, where the dtype is int64:

a = np.arange(2 * 3 * 1).reshape(2, 3, 1)
b = np.arange(1)
paddle.einsum("...i, ...i", a, b)

* Test cases in test_einsum test floating point dtypes only.

As of now Paddle only supports float/double dtypes in matmul, which is
one of building blocks of this Einsum implementation. We decide not to
test einsum against other dtypes.

* Polish format.

* More formatting.

* Format...

* Einsum: improve test coverage.

* Einsum: bug fixes and more testcases for testing error messages

* Einsum: fix format..

* Einsum: fixed typo and format.

* Einsum: format again...

* Einsum: applied suggested changes.

* Einsum API: improve API documentation.

* Einsum API: apply suggested changes.

* Einsum API: Add dygraph only note.

* Einsum API: Add dygraph only note.

* Einsum API: fixed unittest.

* Fix a bug : can't load more than one custom op module

* Fix a bug : can't load more than one custom op module

* add test for load multiple modules of custom c++ op

* add config for Coverage CI

* fix bug of py36 import

* Fix safety-bug of functional.linear

* Fix safety-bug of functional.linear

* Fix safety-bug of functional.linear

* Fix safety-bug of functional.linear

* add recompute for pp

* add recompute offload

* add recompute partition