* 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.

* add hinge_embedding_loss

* fix test_API

* test_API succeed

* add English doc

* fixed using of expired fluid api

* fix doc

* fix doc and rm python/paddle/fluid/layers/loss.py

* get raw python/paddle/fluid/layers/loss.py back

* fix Examples bug in English doc

* unique -> flatten

* fix api code

* fix English doc

* fix functional loss English doc

* fix Example doc

* .numpy() -> paddle.unique()

* fix unique

* fix label_item_set

* modified judgment equation

* Got a beautiful loss equation

* use paddle.to_tensor

* fix loss and add static check

* fix loss and add static check

* delta -> margin

* support data_format='NHWC' for prelu channel mode

* fix dropout static when axis != None

* update dropout test

* add dropout test

* fix test

* Update test_dropout_op.py

* Update test_dropout_op.py

* fix testcase

* fix testcase

* Update test_dropout_op.py

* fix testcase

* fix testcase

* optimize perf

* add new test

* fix testcase

* add zeropad2d v0.1

* add zeropad2d v0.2

* add zeropad2d v0.3

* add zeropad2d v0.3

* add zeropad2d v0.3

* add zeropad2d v0.4

* add zeropad2d v0.5

* add zeropad2d v0.5 codestyle

* add zeropad2d v0.5 codestyle

* add zeropad2d v0.6 functional

* add zeropad2d v0.6 functional

* add zeropad2d v0.6 functional

* Fix the slow running speed of kl_div when option reduction is set

* fix unittest coverage

* modify sparse_attention docs, test=develop

* add warning

* add warning ,test=document_fix

* fix bug:
1. atten: set the default value of attn_dropout_rate to None
2. ffn: add activation parameter

* Revert "Align CTC grad scale same with ESPNet (#34729)"

This reverts commit 10f9644c.

* ctc grad compute on gpu