* change return_numpy[PE] default value

* Remove convert to numpy in unit test

* elementwise_add with bcast: Brian's implementation by Brian added, with default bcasts

* elementwise_add with bcast: GetExpectedKernelType added to elementwise_op

* elementwise_add with bcast: use_mkldnn attribute added

* elementwise_add with bcast: changes after review and some formatting

* elementwise_add with bcast: changes after style check

* elementwise_add with bcast: changes after style check cont.

* elementwise_add with bcast: MKLDNN unittests added

* elementwise_add with bcast: original unittests with use_mkldnn flag

* elementwise_add with bcast: handling of MKLDNN format corrected

* elementwise_add with bcast: setting MKLDNN format turned into lambda

* elementwise_add with bcast: MKDNN format setting turned into separate function

* elementwise_add with bcast: condition for choosing MKLDNN simplified

* elementwise_add with bcast: fix for MKLDNN format set incorrectly in bcasts

* elementwise_add with bcast: changes in unittests for broadcasts

* elementwise_add with bcast: fixes in unittests regarding dimensions

* elementwise_add with bcast: bring back correct format setting in mklml grad path

* elementwise_add with bcast: fixed compilation error

* Fix relu and log

* Update nn.py

* 1. Remove PYTHON_FLAGS from paddle_build.sh in paddlepaddle/paddle:latest-dev

* 1. Add PYTHON_FLAGS back
2. Change SIGKILL to SIGINT and SIGTERM

* 1. Add setup.py.in back

* 1. add pip install open-cv in Dockerfile to avoid libusb_exit hanging up which is caused by the opencv-python package missing

* 1. Add the && \ to line above

* 1. Remove the notice comment

This reverts commit 4d8e8ee2, reversing
changes made to d6a9f005.

1. Add a new attribute named 'startuo_seed' to RandomCropOp. If the input
'Seed' is not initialized, the 'startup_seed' will be used to replace
it.

2. Refine CustomReader. Add a member variable 'scope_' to it. The
'scope_' will act as the global scope of preprocesing, making it
possiable to save something cross batches.

* "add some api reference"

* "fix based on preview"

* "fix evaluator"

* "remove template doc"

* "add doc for exec"

* "add more changes"

* "fix based on preview"

* "chagne code format"

* "add some api reference"

* "fix based on preview"

* "fix evaluator"

* "remove template doc"

* "add doc for exec"

* "add more changes"

* "fix based on preview"

* "chagne code format"

Give assign layer's second parameter 'output' a default value: None. If
it is None, the output variable will be created inside the layer.