* Modified params of some APIs to support tuple and list.

* fixed bug.

* add fast path for p == 0 in dropout

* add ut

* rename manual_seed to seed

* rename xxx1d-->xxx1D, xxx2d-->xxx2D, xxx3d-->xxx3D

* rename manual_seed --> seed

* do not rename .cc, .cu and .h file

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* rename manual_seed --> seed

* disable_static on doc example code

* donot change manual_seed on generator

* add enable_static on sample code

* convert python/paddle/fluid/layers/nn.py to bak

* fix typo

* fix code style

* fix seed to manual_seed when call functions of Generator()

* fix bug

* fix dropout bug in backward when input is 1d tensor, test=develop

* add test case and refine error message, test=develop

* refine error message, test=develop

rename Dropout2D/3D to Dropout2d/3d

* add alpha_dropout in nn.functional and nn.layer, test=develop

* refine Interface and assertion, test=develop

* fix ci import error, test=develop

* fix alias and use layers.scale, test=develop

* fix doc and training params, test=develop

* refine details in doc, test=develop

* fix doc details, test=develop

* [API2.0] add dropout, dropout2d and dropout3d, test=develop

* refine Interface and assertion after review, test=develop

* fix alias p=1 and use scale, test=develop

* fix doc and training, test=develop

* fix doc in Dropout2D, test=develop

* change several tests to use the right parent class, test=develop

* add dtype for TestLoDTensorAndSelectedRowsOp, test=develop

* add seed op

There are PythonAPI tests in Op's unittest which don't need to inherit OpTest class.

* add error log

* refine_dropout_mem,test=develop

* # This is a combination of 14 commits.
# The first commit's message is:
remove ut test_dist_word2vec in mac ci, will fix it in private, test=develop (#17066)

# This is the 2nd commit message:

Fleet unify distributed training (#16791)

* implement distributed transpiler with fleet
# This is the 3rd commit message:

ParallelDyGraph with GPU collective mode (#16827)

implement dygraph.parallel.DataParallel to hook reduce op.

# This is the 4th commit message:

Init mixed precision training interface (#16856)

* Init mixed precision training interface

* Add fp16 test script

test=develop

* All initializers support float16

test=develop

* Code cleanup & add more code annotations

test=develop

* Update API spec

test=develop

* Add usage example in doc

test=develop

# This is the 5th commit message:

fix reference_count_pass,test=develop (#17060)

test=develop
# This is the 6th commit message:

Speedup roi_perspective_transform op by caching the information of linear interpolation in forward (#17090)

* Cache the information of linear interpolation in forward and use it in backward.
test=develop

* Fix cuda kernel.
test=develop

# This is the 7th commit message:

remove unnecessary prepare_data (#17080)

test=develop
# This is the 8th commit message:

fix interpolate cu. test=develop (#17101)

# This is the 9th commit message:

test=develop, double backward leaky_relu (#17067)

backward of backward: leaky_relu
# This is the 10th commit message:

fix fuse optimizer ops (#17102)

test=develop
# This is the 11th commit message:

truncated_gaussian_random supported in distributed training, test=develop (#17091)

# This is the 12th commit message:

 Detailed coordinate description for yolov3 loss (#17007)

* Detailed coordinate description for yolov3 loss

test=develop

* modified api.spec

test=develop

* modified loss name

* fix api.spec

test=develop

* polish description

test=develop

* modified api.spec

test=develop

# This is the 13th commit message:

fix test_weight_decay (#17109)

test=develop
# This is the 14th commit message:

Path flag (#17105)

* fix python/paddle/fluid/__init__.py detecting problems

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

* is_training to is_test in dropout op

* handle dropout and batch_norm operator when prune pdesc in testing mode

* handle dropout and batch_norm operator when prune pdesc in testing mode

* add get_inference_program method

* fix dropout op

* fix ci

* test data after each batch training

* refine code

* refine test_book3

* fix ci

* follow comments

* init commit

* change some dir name

* Simplize Gradient Check

* Stash

* Extract apply_backward_pass to backward.py

Rename apply_backward_pass to append_backward_ops

* Use graph API to check gradient

* Fix ci

* Fix CI

* Fix backward for double precision

* Stash

* Fix CI

* Fix ci

* Ignore GRU test

* Ignore xe op

* Fix CI

* Fix softmax with xe gradient

The correct equation should be IG = OG * (d_softmax_with_xe())

* Fix typo

* Fix merge error

* Disable LRN

Change type of dropout_prob to template typename.