* Add the calibration tool code for int8 inference and focus test.

* Fix the calibration tool per the review comments.

test=develop

* Update the calibrator doc and remove extra line.

* Fix the invalid is_negative_input attr set on Mobilenet.

* Add the comments and fix the format issue.

test=develop

* Update the CMakelist.txt for Calibration PR.Disable the Calibration UT if not enable MKLDNN.

test=develop

* Update the CMakeList.txt.

test=develop

* Disable the test_calibration case on WIN and MAC.

test=develop

* Add the missing brackets.

test=develop

* Remove the outdated map operator which not supported on Python3.

test=develop

* Fix the style issue.

test=develop

* 1.Update the CMakeList.txt to disable calibration tool ut when the WITH_MKL is not set;
2.Add the workaround to enable the FLAGS_use_mkldnn for PR_CI(PADDLE).

test=develop

* Fix the typo and format the License header.

test=develop

* 1.Add and Update TODOs per review comments.
2.Code clean.

test=develop

* Update label role implementation to use new API

* Try trainable embedding layer

* Fix feed order

* Add infer call

* 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

Unify the recognize_digits

* py_test support argument, test_image_classification_train support argument

* use REMOVE_ITEM to rm item from list in cmake

* init commit

* change some dir name

add concat op with CPU kernel

* init add

* add topk op

* someupdate

* fix style check

* add test py file

* update top k cuda kernel

* follow comments

* remove debug print

* fix casting error

* fix casting error

* fix casting error

* fix rename bug...

* fix travis

of identity to Y.

1. finish lookup table CPU and GPU kernel
2. Add some cuda helper
3. Add some math funtor