* fix init_gflags with 'python -c', test=develop

* fix pruned_program_cache_key of Operator, test=develop

* Make the place parameter default

test=develop

* Make the place parameter default

test=develop

* Make the place parameter default

test=develop

* Make the place parameter default

test=develop

* Make the place parameter default

test=develop

* Make the place parameter default

test=develop

* Make the place parameter default

test=develop

* Make the place parameter default

test=develop

* static model runner basic implement, test=develop

* add run program op to execute loaded program, test=develop

* refactor static model runner & run program op, test=develop

* reset engine.cc to resolve conflict

* adapt the change of dygraph double grad, test=develop

* refactor impl to solve control flow error, test=develop

* clear debug code, test=develop

* fix ci str compatible error & checkout dygraph grad maker & add example, test=develop

* hide api & add op test, test=develop

* fix run program op test places error, test=develop

* fix program by review comment, test=develop

* delete change var desc name, test=develop

* fix other program by review comment, test=develop

* remove _static_graph_guard, test=develop

* add selectedrows test, test=develop

* remove desc parser, test=develop

* fix detail program, test=develop

* change socpe create & add test, test=develop

* prune train program by fetch_list, test=develop

* add unittest for prune, test=develop

* fix pruned feed, test=develop

* support ParallelExecutor and feed prune, test=develop

* add comments, test=develop

* update unittest, test=develop

* update unittests, test=develop

* remove debug code, test=develop

* support cond in clone, test=develop

* support cond in prune, test=develop

* support multiple minimize, test=develop

* support cache, test=develop

* fix _copy_param_info_from, test=develop

* support python2 str, test=develop

* remove debug code, test=develop

* fix bug of caching CompiledProgram, test=develop

* fix multi_device issue, test=develop

* tmp

* support tuple in fetch_list and overriding use_prune, test=develop

* dont use nonlocal in python2, test=develop

* remove nonlocal, test=develop

* code clean, test=develop

* code clean, test=develop

* feed list, test=develop

* test adam, test=develop

* follow comments, test=develop

* reduce duplicate code, test=develop

* update comments, test=develop

* support feed_python_builtin, test=develop

* add test, test=develop

* support CompiledProgram, test=develop

* support fluid.data, test=develop

* fix ci problems, test=develop

* follow comments, test=develop

* sequential reader stage 1, test=develop

* fix ut, test=develop

* fix iterable=False reset bug, add some logs and polish code, test=develop

* inference feed partial data, test=develop

* Turn on keep_order=True for test, test=develop

* enhance ut to test more cases, test=develop

* test commit for reverting

* Revert "test commit for reverting", test=develop

This reverts commit 80aef42e.

* add ut of merged and unmerged results, test=develop

* add more uts for coverages and add en doc of api, test=develop

* follow comments, test=develop

* change note style, test=develop

* update ScopeBufferedSSAGraphExecutor&AsyncSSAGraphExecutor&ThreadedSSAGraphExecutor&FastThreadedSSAGraphExecutor&ParallelSSAGraphExecutor&ParallelExecutor for fetching unmerged results.

* add the unit test for fetch_unmerged.

* update ut for multi-card and multi-cpu.

* add the error message and the user suggestion in FetchOpHandle. test=develop

* add half_async in the communicator
* fix DistributedStrategy

* polish executor hint message, test=develop

* fix punctuation error, test=develop

* Add a single_process_multi_thread transpiler.
* Add some UTs.
* Fix some API description.

* fix fetch handler problem and refactor
when a user define FetchHandler class, he or she should initialize a handler
with variable dict. the key of a variable dict is a user defined name,
the value of a variable dict is a Varaible generated from python API.

For each fetching, a user should implement handler function in which
fetched_result_dict will be available and the user can access the fetched value
with user defined keys.

* bug fix, test=develop

* Refine the cache of program, context and scope in executor.
test=develop

* Refine the unittest test_executor_and_use_program_cache.

* Add the test the PaddingRNN with use_program_cache=True.
test=develop

* Remove a check.
test=develop

* Refine the unittest to check whether it is correct when setting use_program_cache=True.
test=develop

* fix fetch handler error with pslib
* fix distributed lookup table op with 1 pserver

test=document_fix

* fix en doc train_from_dataset and infer_from_datatset

* fix fluid.data
test=document_fix

* fix doc batch dim
test=document_fix

* polish executor doc
test=develop

Refine error message for new data API

add executor.FetchHandler for train/infer from the dataset

* shape and optimize paddle error message stack, test=develop

* limit exception type & add unittest, test=develop

* fix multi-platform problem, test=develop

* fix related unnitest failed, test=develop

* add doc & fix unittest errors, test=develop

* fix function name error, test=develop

* update tensor test exception msg compare, test=develop

* remove unittest on win32, the dir format is different, test=develop

* remove useless package, test=develop

* add paddle enforce handler unittest, test=develop

* add exception checkout, test=develop

* fix coverage failed, test=develop

* fix op registry test failed, test=develop

* refactor whole pr, test=develop

* remove test in CMakelist, test=develop

* fix coverage, test=develop

The new "fluid.data" changes old "fluid.layers.data":

1. Add shape and dtype check.
2. Remove "append_batch_size" parameter. We won't offer this in the new data layer because other deep learning platforms don't have this kind of data layer pre-processing. It may confuse users.
3. Remove "stop gradient" parameter because the data layer doesn't do back-propagation

TODO：
Now data layer feeded by executor is checked, will we want to check the feed data of readers in the future?

* support change shuffle thread num
* support change train thread num
* fix receive shuffle data of each channel
* data norm stop gradient
* add check thread_tensor type and root_tensor type when merge metric
* remove sleep in shuffle, add config
* add config of pslib client to client communication
* fix xbox str
* add data norm op testcase
* add flush in trainer finalize

test=develop

* update executor feed

* use PE for compiler
test=develop

* fix memory overlapping of fetch var (return of executor.run), test=develop

* fix wrong usage of ParallelExecutor in op_test, test=develop

* remove useless parameter and simplify code

* avoid tensor destruct untimely, test=develop

* add testcase independent of OpTest, test=develop

* update exe.run

* remove legacy memory optimization codes, test=develop

* follow huihuang's comments,test=develop

* follow luotao's comments, test=develop

* feature/buffer_shared_inplace, test=develop

* refine code, test=develop

* fix elementwise_add op cpu inplace and sum inplace bug, test=develop

* add unittest and debug log, test=develop

* fix parallel_executor scope bug, polish code, test=develop

* fix sum op, activation op, single_in_place_inference bug, test=develop

* remove kLocalExecScopeName, test=develop

* fix unittest,test=develop

* fix out_var first version bug, test=develop

* follow comments,test=develop

* enhance execution error info
test=develop

move the thread-check code from train_from_dataset to a single function
add UT for the thread check function

(1) use channel instead of vector/BlockingQueue in Dataset，to keep same with existing implementation, and make code more readable and flexible (dataset single output channel or multi output channel). one previous memory out of limit problem is cause by not release memory after training.
(2) add Record because MultiSlotType costs too much memory (80B)，fix memory out of limit problem.
(3) add Channel, Archive in paddle/fluid/framework
(4) change dataset from shared_ptr to unique_ptr in pybind
(5) move create/destroy readers from trainer to dataset
(6) move shuffle from datafeed to dataset. dataset holds memory, datafeed is only for load data and feed data to network.
(7) fix thread num bug of Dataset when filelist size < thread num
(8) support set_queue_num in InMemoryDataset