* Enhance reduce op for multi dims.

* Uncomment some unitest.

* Uncomment unitest.

* Remove unused code.

* Fix infershape and python wrapper.

* Add more examples.

* Fix l2_normalize.

* Fix normalization_wrapper.

* Polish code.
1. Rename unitest function.
2. Rename const variable.

1. If all bboxes are not difficult ground truth, the users can not define the data layer for this flag and not the input can be None for detection_map API.
2. Set default value for aspect_ratios in prior_box API.
3. Add more check in prior_box API.

* Added kernel to is_empty_op

* Added python API

* Updated code as required

* Updated unittests

* package prior_box op

* add doc

* add unittest

* add unittest

* fix CI fails

* listen_and_serv use localscope

* fix ut

* "fix ci"

* "fix network config"

* "rerun ci"

Change default split minimize value to speed up transport data to pserver

* add dist transpiler unit test

* update by comment

* update by comment

* fix ci

* fix ci

* Update the mnist test cases with the new API syntax.

* Turn on the tests for MNIST

* delete the test files got merged accidently.

* Enable the mnist tests. ready for test driven development.

* Comment out the infer first
This is to confirm that the Trainer.train is working

* Add CMake file to include the tests

* Make the train program only return avg_cost for now

* Update the tests to use the latest syntax

* add Inference.infer

* optimize code

* update no_test_word2vec_new_api.py

* update trainer

* split check_and_get_place

* use inference_program to save inference model in Trainer

* update demo

* update save_inference_model

* clean code

* a draft of trainer.test()

* polish trainer.test()

* polish trainer.test()

* update code format

* update

* polish code

* polish code

* polish code

* Make trainer.test follow the rule of returning [loss, metric, metric, ..]

* "add float64 tests"

* "fix based comment"

* "fixed based comment"