* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

* polish code comments

* polish data_device_transform.cc

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* use yapf to format all python file

* yapf exclude two unittests file for they rely on writing and reading file, and format will break them

* disable diff_py_file because too many diff files cause command following failed

* Dynamic graph support to Automatic SParsity.

1. Added dynamic support to ASP module (paddle.fluid.contrib.sparsity).
2. Added ASP related unit-tests regards to above changes.
3. Put ASP module under paddle.static for now, waiting for APIs confirmation from Paddle.

* Modified documents of functions to have correct examples.

* Update in_dygraph_mode to paddle.in_dynamic_mode()

* Modified documents of functions and added comments

* Minor changes.

* Fix example errors in asp API.

* Code Change for Review

1. Added more examples in documents.
2. Chaged test_asp_pruning_static.

* Minor changes

* Update ASP function documents.

* Update ASP function documents.

* Reduce test case size of asp pruning due CI time limit.

* Update time limitation to some asp UTs.

* Fix sample code errors.

* Fix sample code errors.

* Fix sample code errors.

* Update time limitation to parts of ASP UTs.

* Update UTs to fit with CI.

* Reduce problem size in python/paddle/fluid/tests/unittests/asp/test_fleet_with_asp_dynamic.py

* Added paddle.asp

* Fixed type casting error of OpRole.Optimize in new dygraph mode.

* Made set_excluded_layers be compatible with 2.2

* Fix example code of calculate_density.

* Update code examples.

* Move paddle.asp to paddle.incubate.asp

* Fixed an example error of calculate_density

Sparse tensor core for convolution requires the input channel dimension is 2:4 structed sparse.
So we have to mask the input channel dimension for using sparse tensor core