* add memory_analysis

* fix has_none

* add pool2d convert test

* modify error

* modify error

* modify error

* modify error

* modify error

* modify error

* sparsity support

* fix BatchNorm for fp16

* update

* update

* update

* try make CI pass

* doc typo

* update doc string

* A leap of try for cudaLaunchCooperativeKernel

* fix bugs

* Totally replace the lar cuda kernel

* Fix bugs

* a test for lars merge

* Adding las_op_momentum infer_shape

* Fix codes

* use avg_numel instead of max_numel to acquire grid num

* modify unittest files about lars op

* Finally converge when merged-lars works

* fix ctest files

* add merged_operation kernel when cuda version is older than 11

* Fix code style

* fix ctest failure

* fix error

* fix all ctest error and change lars compute code of cpu

* fix bugs on v100.

* revert python modififation about lars

* revert python modification codes

Check detail PR description at https://github.com/PaddlePaddle/Paddle/pull/36116

* add attr is_distributed

* refine code

* refine black/white list for pure fp16

* add fp16 for clip_by_norm api

* support ClipByGlobalNorm for fp16 in dygraph

* add unittest for dygraph clipGlobalNorm

* refine unittest for dygraph clipGlobalNorm for mac and windows

* refine unittest

* add unittest for fp64

* refine unittest for fp64

* pool fix

* comments

- Lint

- Merge with develop

- lint

* refine amp level

* fix typo

* update tracer._amp_level

Remove RunFromCinn method in PE because We Will Call CinnRunner in Compute method of SubgraphOp

* native commit for triple grad of sigmod

* Updated unittests files

* init functional jacobian api

* Updated trible_test func

* Updated gradient_checker & test_script

* finish test with dtype float32

* add float64 test case

* polish code

* use atol=1e-5 with dtype float64

* fix for ci

* set timeout for test_jacobian

* fix dygraph grad to support high differential

* polish API docstring

* Updated gradient checker and some related files

* fix double grad strip error for high differential

* fix double grad strip error for high differential

* Add Sigmoid triple grad tests

* fix dygraph double grad dtype error when calling for high differential senario

* Updated triple grad teses func

* Use np.random to initialize ddx

* Updated triple_grad_check func

* add todo for gradient checker and refine some comments

* remove additional code

* add test for warnging in backward.py

* format python code
Co-authored-by: Nveyron95 <veyron_wu@163.com>
Co-authored-by: Nlevi131 <limaolin01@baidu.com>

* add_int_pass

* add_int8_flag_pass

* add_int8_flag_pass

* fix CMakeLists.txt

* fix test_trt_fc_fuse_quant_dequant_pass.py

* fix python/paddle/fluid/tests/unittests/ir/inference/test_trt_fc_fuse_quant_dequant_pass.py

* fix test_trt_fc_fuse_quant_dequant_pass.py

* add alexnet

* modify format

* modify format

This reverts commit b3f6eedb.

* change the paddle.mm to matmul_v2

* update the code for the mm

* update the document for the mm

* [NPU] modify for model deepfm

* [NPU] unit test delete precision control

* [NPU] add more unit test

* revert elementwise_mul related modification

* [NPU] add more unit tests for concat

* change time to remove static tempfile

* delete remove_static_file() function

* autograd.functional passed pylint checker.

* autograd.functional: fix import errors.

* autograd.functional: fixed unit tests.

* autograd.functional minor format change

* [NPU] fix elementwise_mul to support broadcast, test=develop

* remove debug files, test=develop

* add axis support, test=develop