test=develop

* fix ramdom fail
test=develop

* enable recurrent op test=develop

* Generated functions can take `*args` as inputs.

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

* add copyright hook

* add copyright hook

* refine copyright hook

* "test copyright hook"

* fix check style

* fix ci

* Make param_attr as a strong typed class

Fix #5819

* "add asnumpy interface"

* Just for unittest

* Change unittests for numpy I/O

* Fix CI

* Change all `data_type` in Python to `dtype`

* Change `date_type` in C++ to `dtype`

* Refine

* init commit

* change some dir name

* Init commit

* Make executor use ProgramDescBind

* Change Attribute from BlockDesc to BlockDescBind

* Since we will get the program desc in RNN, just BlockDesc is not
  enough.

* Add DeviceContext to Executor API

* Rewrite RNN

* Pass Python

* AddBiasOp does not care num_flatten_dims

* Stash

* Fix MacOS Compile

* Pass RNN forward

* add python test

* refactor test

* Make compile pass

* add gradopmaker

* First draft done

* Polish code

* add grad op maker and grad infershape

* Polish code

* Fix backward.cc bug

* Fix infershape

* Rename function

* add backward test

* simplify recurrent test

* Update

* Pass unittest

* Add comments & refine test

* Add comments

* refactor test

* Complete Unittest

* fix StepScopes enforce

* Remove unused unittest

* no type error

* Update

* Make RNN Pass unittest

* add sparse support for sum op

* typo fix

* fix gpu build error

* fix unittest error

* typo fix

* infer var type and shape in op_test

* follow comments

* fix build error

* bypass some unittests depend on NetOp

InferShape in Operator should be performed in OperatorBase::Run.

* cond_op, recurrent_op and mnist might be changed in following PR

* remove alias

Fix #3582

* make stepnet member

* add pybind support

* fix Inputs Outputs

* remove unique_ptr