* add public_python_api in prim test

* fix test_squeeze2_op

* wisemax fp16 support

* add bf16 support 4 elementwise_max

* append broadcast 4 op 4 fp16 / bf16

* fix elewise_max ut bf16 numeric delta

* append fp/bf16 uts

* add fp/bf16 uts

* change bf16 uts delta

* fix some issue

* add prim 4 fp16

* refresh

* compat

* register

* testop

* fix

* fix

* fox

* cast

* cast

* fix

* type

* fix

* out

* cast

* fix

* fix

* fix

* broad

* broad

* broad

* fix

* fix

* fix

* fix

* fix

* broad

* broad

* numel

* fix

* fix

* fix

* fix

* cinn

* fix

* fix

* fix

* fix

* isort all files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* 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

* 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

* add yaml for ele_max ele_min

* fig

* push

* xxx

* add elementwise_max & unittest

* refine cuda register and unittest

* refine unittest

* refine uinttest for bf16

* refine optest

* refine code

* refine unittest

* refine unittest

* update ops's unittest of elementwise_pow, elementwise_max, elementwise_min, scale and sqrt
1. update elementwise_pow, elementwise_max and scale's unitests with input data type (float32 -> float64)
2. fix bug that the elementwise_pow doesn't meet threshold requirements with tackling float64 data
3. remove sqrt from op_accuracy_white_list.py
4. update the unittests of elementwise_pow, elementwise_max and elementwise_min ops that their input data shape over 100
5. test=develop

* modify the writing style according suggestions
test=develop

test=develop

* fix input shape of op tests for elementwise_sub,
gather, pad2d, transpose, softmax, scale,
elementwise_max, hierarchical_sigmoid, reshape2,
sign, squeeze, reduce_sum, sum, squeeze2,
unsqueeze, unsqueeze2, cast, reverse

test=develop

* fix cast, elementwise_mul, gather, scale, sign,
softmax, transpose

test=develop

elementwise broadcast function enhancement

Currently, our tests run with 2 GPUs, the init time is absurdly long:
about 4s for each process.  Currently, we run each OP test on
different processes. This PR:

1. create cmake function py_test_modules which will generate the
Makefile that runs a list of Python unittest module in a single Python
process.

2. move all "python unittest compatible" (e.g., used the unittest
package, not just a regular python file). from fluid/tests to
fluid/tests/unittests.

3. cmake now will run all OP tests in fluid/tests/unittests in a
single process, except the time-consuming tests, they are separated
into different processes to utilize parallelism. Please make sure to
use the unittest package if you put the python test file in
fluid/tests/unittests

4. remove all exit(0) from fluid/tests/unittests/*.py, exit(0) is used
to disable unittest, we can not do it when running all tests in a
single process since it will terminate the process without running the
other tests. Instead, the test is disabled in
fluid/tests/unittests/CMakeLists.txt. FIXME is added for each disabled
item. Please disable the unittest from
fluid/tests/unittests/CMakeLists.txt, instead of adding exit(0) to the
Python file, for all Python file in fluid/tests/unittests/.

5. add an option WITH_FAST_BUNDLE_TEST. When OFF, will run the unit
tests in separate process so that they can be tested individually.

* "fix decode bug"

* "follow commnet"

* "fix error"

* "fix hook bug"

* fix based comment

* fix copyright

* fix based on comment