* fix bug of py36 import

* remove unmatched signal error stack

* fix error writing for cond

This reverts commit 0a5c99e8.

This PR adds fused transformer related files defining c interface including class, function etc..

* 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

* [NPU] Support npu op expand_v2 and expand_v2_grad

* [NPU] Support npu op expand_v2 and expand_v2_grad

* [NPU] Support npu op expand_v2 and expand_v2_grad

* update test_expand_v2_op_npu.py

* update test_expand_v2_op_npu.py

* modify expand_v2_op_npu.cc

* modify expand_v2_op_npu.cc

* add det_mv3_db & LeViT test case in pr-ci-inference

* fix LeViT model dir bugs

* fix grammar error

* - Added softmax without caching

* - Binary is no longer manually cached

* - Activation onednn caching removed

* - Removed manual caching of activation

* - modified UT

* - fix

* - fix

* - fixes to building

* - fix

* - fix

* - fix to UT

* - Faulty UT workaround

* - approval workaround

* - Fixes after review

* - compilation fixes

* - more lint fixes

* - more fixes after review

* - fixes after another round of review

* add state_dict and load_state_dict and unittest for class GradScaler

* refine unittest for coverage of load_state_dict

* refine comments of code-block

* refine some comments

* refine state_dict code and unittest

* add #require gpu, xpu for GradScaler get/set example code

* add #require gpu, xpu for GradScaler get/set example code

* refine example code

* refine unittest for state_dict

* refine unittest for state_dict

* fix bug of DataLoader in TestGradScalerStateDict

* add flag FLAGS_cudnn_deterministic

* add set_value_grad op

* add unittest.

* polish unittest.

* polish code.

* support cuda kernel

* polish code according to CI

* polish code.

* polish code

* remove *.pyc

* polish code.

* add unittest to improve coverage.

* polish code.

* fix_fc_reshape_convert

* fix

* add while read_from_array write_to_array npu op

* optimize unittest

* add momentum_op_npu and test

* update

* fix hang

* add reduce_mean_op_npu and test

* remove skip.If

* update

* add batch_norm_op_npu and tests

* remove skip.If

* fix bug

* Add ext_tensor.slice() API, test=develop

* Call Tensor::mutable_data first to fix bugs and add test for writing to sliced tensor

* Fix unit test bug

* Fix code format problem, test=develop

* Fix code format problem

* Fix code format problem

* strengthen unit test

* Use CustomTensorUtils::ShareDataFrom to simplify codes

* add auto_parallel apis

* add save/load for pipelineparallel

* add save/load

* add exp and exp_grad npu op

* modify support register type

* remove empty line and remove exp_grad support data type int/int64

* move exp and epx_grad kernel to activation_op_npu.cc, delete attrs

* move code to activation_op_npu.cc

* Add NPU kernel for TopKV2 op

* deleted unnecessary cache file static_mode_white_list.cpython-37.pyc

* A draft for error checking

* A commit with accuracy error for float32 data

* Modify codes according to the review comments

* Modify codes according to the review comments

* add not used output var to gc_check_list; test=develop

* add useless output to gc check list; test=develop

* fix npu compile error, test=develop

* [NPU] Support npu kernel for flatten_contiguous_range op, test=develop

* [NPU] Support npu kernel for flatten_contiguous_range op, test=develop

* [NPU] Support npu kernel for flatten_contiguous_range op, test=develop

* [NPU] Support npu kernel for flatten_contiguous_range op, test=develop

* [NPU] Support npu kernel for flatten_contiguous_range op, test=develop

* [NPU] Support npu kernel for flatten_contiguous_range op, test=develop

* [NPU] Support npu kernel for flatten_contiguous_range op, test=develop

* Update flatten_op_npu.cc

* Update flatten_op_npu.cc
Co-authored-by: Nqili93 <qili93@qq.com>

添加Kernel primitives api： ReadData, WriteData ComputeFunctor