* fix mac build error

* enhance memory optimize transpiler to let users set to some skip opt set of variables

* Add mean_iou op.

* Add unitest for mean iou op.

* Add optional collections of confusion matrix and mean_iou.

* Fix cuda kernel.

* Refine code.
1. Merge computing in GPU to two kernel.
2. Use wrong array and correct array instead of confusion matrix.

* Add python api and fix cuda kernel.

* Fix comments.

* Small fix.

* Small fix.

* expose h0 in dynamic_lstm

* update by comment

* update by comment

* h0 to H0

* less_than
* cumsum
* multiplex
* open_recordio_file

* 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.

* Add slice op.

* Remove using from header file and fix doc.

* Fix doc

* Small fix.

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

* 1. add weight decay feature into fluid benchmark test
2. add learning rate decay feature into fluid benchmark test
3. add L1&L2 regularization feature into fluid benchmark test
4. add error clipping feature into fluid benchmark test
5. add gradient clipping feature into fluid benchmark test

* Add some document to README.md under benchmark/fluid/ repo

* Add model_base.py

* Fix bugs in test_listen_and_serv_op

* 1. remove args out of fluid_benchmark.py
2. remove lr_decay, regularization, clipping out of fluid_benchmark.py

* add async_mode description to doc and remove the clipping description out

* for restart build

* to restart build

* remove optimization args from args.py

* 1. remove optimization from models
2. fix bug in test_listen_and_serv_op

* change the name retry_times to left_time

* change retry_times to the pserver start left time