* add the weight decay func for the momentum op

* Add the multi_precision function in Momentum Optimizer.

* Make sure that the initial value of master weights are same with the fp16 weights.

* add static loss scaling.

* add the rescale_grad function in the pure fp16 training.

* use the original momentum updating method.

* Polish some codes, such as variable names.

* add docstring for apis.

* update the var creation details of _create_master_weight.

* not modify codes about imperative momentum updating.

* Fix the error of test_dist_sparse_tensor_load_momentum UT.

* add unit test for multi precision fp16 training.

* add more unit tests for CI.

* Use lower threshold values for allclose comparing in test_multi_precision_fp16_train UT.

* For CI Coverage Checking.

* disable ut test_parallel_executor_fetch_isolated_var,test=document_fix

* test for limiting ut exec time as 15S

* fix an error caused by cannot find ut

* fix some error

* can not find test_transformer

* fix error caused by ut not run in windows

* fix error caused by Compiler Options

* fix error caused by setting timeout value as 15 in python/paddle/tests/CMakeLists.txt

* setting timeout value to 120s for old ut

* add the timeout value setting

* fix error caused by ut only run in coverage_ci

* add analyzer_transformer_profile_tester

* fix some error

* fix some error

* fix error with inference option

* fix error with inference option setting as ON_INFER

* add some ut to set timeout

* modified some option

* fix error

* fix some timeout error

* fix error

* fix error

* fix timeout for test_analyzer_bfloat16_resnet50

* fix error

* setting timeout properity for some ut

* first pr for new ut timeout as 15S

* Split test_calibration test to two tests

test=develop

* Modify CMakeLists file
test=develop

test=develop

1.Remove the code for setting mkldnn environment in the test_calibration.py;
2.Update the cmake file for MKLDNN environment enabling;
3.Update the INT8 inference doc.

test=develop

* 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