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"

* Put all new tests under high-level-api

* be consistent with the naming