Fix a multi-thread bug in readers

add initial memory flag in MB for infer

fix bugs in fluid_benchmark

Refine prefetch

* wip

* use executor.complete to end trainer

* fix build

* fix build with distribute off

* fix typo

* fix cmake typo

* fix build

refine docs of elementwise_op etc.

* enable docstring checker and fix comments

* update

* update by comments

* fix build

* Add normalization operator.
1. Refine the raw norm_op and let it more general to support to normalize Tensor along any axis.
2. There is a bug in l2_normalize API, which lacks sqrt after `reduce_sum`.
3. Use norm_op to refine the l2_normalize API.
4. Fix bug in test_normalization_wrapper.py.

* Create dynamic_graph.md

* Update dynamic_graph.md

* Update dynamic_graph.md

* Update dynamic_graph.md

* follow comments, add graph

* Update dynamic_graph.md

* Update dynamic_graph.md

Build: add make before make install to catch up CMakeLists change.

* Add slice op.

* Remove using from header file and fix doc.

* Fix doc

* Small fix.

Make status update thread-safe

Enable CPU on Parallel executor

The status is updated in the Process() thread
and can be checked in another HandleRequest() thread.

* "add inplace attribute"

* "register inplace attribute"

* "change se-next model for memory-reuse"

* "fix typo"

* repick

* fix merge conflict

* "fix stupid error"

Fix fluid_benchmark stacked_dynamic_lstm model error

MKLDNN layout: Support for pool operator

replace use_event with use_cuda, because use_event means the program running with CUDA, so use_cuda maybe more intuitive.