* Add yaml config

* Add yaml for flatten_contiguous_range_op

* Remove h_sigmoid yaml

* Fix CI errors

* Fix code format

* Fix flatten OP errors

* Fix conflicts

* Fix CI errors

* Remove flatten_contiguous_range OP

* Remove redundant code

* Fix typos

* add yaml for ele_max ele_min

* add yaml for: mish / logexpsum / expm1 / elemenwise_pow / elementwise_floordiv

* 1. add the python api grad 2. add final and intermediate state vlog 3. change the python_api error logic

* add python api or close the check_eager=True

* fix the compatibility

* add nll_loss yaml

* fix nll loss

* fix nll loss bug

* fix bug

* fix bug

* fix infrt problem
Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* [Refactor] refactored eager_gen.py PR #2

* [DoubleGrad PR #1] Decoupled code generation logics for Dygraph ForwardFunctions and GradNodes

* Fixed minor issue

* Adjusted logics of GenerateNodeCreationCodes and GenerateForwardDefinition

* Fixed issues

* Supported higher-order grad node generation

* [DoubleGrad PR #4] Supported higher-order GradNode generation

* [DoubleGrad #4] Bug Fixes to Double Grad Node Generation

* Fixed yaml typo

* Fixed yaml typo

* fixed minor issues

* Fixed minor issue

* fix error; test=develop

* update

* close some yaml

* fix backward attrite error; test=develop

* add div test

* polish code; test=develop

* update

* update

* fix bug

* update bitwise code; test=develop

* update

* update

* fix some bug

* update

* revert cmakelist

* fix optional bug;

* fix bug

* fix bug;

* add backward test

* open bn

* update

* update

* revert eager_gen

* polish code

* fix topk error

* update

* update

* fix bug;

* move label smooth, nll loss

* revert topk

* fix topk label smooth bug;

* remove batch_norm

* remove topk

* change flip infer meta

* fix flip bug

* update yaml

* close abs

* fix histogram bug

* fix histogram bug

* add abs

* fix histogram kernel

* remove expand

* refactor eager flags

* fix flags error when we switch from eager to dygraph

* fix ci problem

* fix ci

* fix ci

* merge develop and fix code style

* merge develop and fix code style

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* merge develop

* support inplace in eager_final state

* little change

* little bug

* add add yaml

* add elementwise add yaml; test=develop

* add norm

* update

* add some yaml config; test=develop

* fix bug; test=develop

* fix compare error; test=develop

* revert erger_gen.py

* update; test=deveop

* remove usless code; test=deveop

* fix bug; test=develop

* fix test error; test=develop

* remove int_type; test=develop

* fix type error; test=develop

* format; test=develop

* remove type register; test=develop

* polish code; test=develop

* fix ci error; test=develop

* move one hot to phi; test=develop

* fix bugs; test=develop

* fix bugs; test=develop

* add infer meta; test=develop

* fix bugs; test=develop

* resolve confilct

* resolve confilct

* fix bug;

* fix error; test=develop

* update; test=develop

* polish code; test=develop

* add one api in eager mode; test=develop

* add one hot test; test=develop

* remove use less code; test=develop

* fix bug; test=develop

* polish code; test=develop

* polish code; test=develop

* fix fold python examples, test=develop

* fix size type, test=develop

* fix python example, test=develop

* fix fold shape check

* fix fold dygraph mode, test=develop

* fix 'invalid escape sequence'

* fix assert error

* fix 'is with a literal'

* fix typo

* change dtype of pooling mask to 'int32' for Paddle2ONNX

* empty commit to rerun ci

* fix format

* optimize conv1d forward

* add conv opt

* Optimize memory copy

* delete share data with

* set num_filters=512

* add nlc optimize

* Optimize num_filter=512 data on A100 and V100

* Fix the workspace_size size setting of filter

* add more int id type support for embedding

* add ut

* add more ut

* fix ci error

* support 5d for nearest

* update nearest3d unittest, test=develop

* fix approve ci, test=develop

* fix approve ci, test=develop

* add maxunpool3d op

* update doc for maxunpool3d op

* update doc for maxunpool3d op

* update doc for maxunpool3d op

* update sample code for maxunpool3d

* add maxunpool1d op

* update some code for maxunpool1d

* add mish operator and api

* remove redundant code and modify grad_atol of mish unittest

* modify mish code to be consistent with other activation implementation

* add fold opereators, test=develop

* add fold opereators, test=develop

* add fold opereators, test=develop

* update fold op error test, test=develop

* fix unitext, test=develop

* fix unitext, test=develop

Add key_padding_mask and attn_mask in sparse_attention Api

1.Key padding mask is a tensor with dimensions [batch_size, seq_len], and attention mask is a tensor with dimensions [seq_len, seq_len]. The data types of the two masks are consistent with Q, K, and V, which are float32 or float64. If the value in Mask is 0, it means that the position needs to be masked.

2.The changed files are mainly paddle/fluid/operators/sparse_attention_op.cu and python/paddle/fluid/tests/unittests/test_sparse_attention_op.py. sparse_attention has three parts: sddmm, softmax, and dsd. Adding the mask operation only needs to modify the softmax. It has no effect on the other two parts. In addition, in order to test the mask function, related tests has been added.