* error message of NCE API enhancement

enhanced ops: unsqueeze, squeeze2, strided_slice, unsqueeze,
unsqueeze2, var_conv_2d, spectral_norm, slice, match_matrix_tensor,
nce, pad, pad_constant_like, filter_by_instag

sequence_expand_as, squared_l2_distance, gather_nd,
center_loss, rank_loss, conv_shift, spp,
modified_huber_loss, smooth_l1_loss, multiplex,
sequence_softmax, nce, huber_loss, group_norm,
kldiv_loss, hinge_loss, expand_as

test=develop

* fix python API tests that do not need to inherit OpTest, test=develop

* fix fp16 cases that will only be enabled in GPU mode, test=develop

* remove TestSoftmaxFP16Op from test cases of softmax_mkldnn_op, test=develop

* fix tests so that the cases are only created in GPU mode, test=develop

* Add detailed error messages for nce layer

test=develop

* Fix some problems

test=develop

* Fix unit test coverage

test=develop

test=develop

* Fix truncated normal.

* Fix.

* Make nce support more distribution.

* Fix API.spec.

* Fix python API.

* Fix.
test=develop

* Fix API.spec
test=develop

* Fix sampler.

* Fix order of arguments in python API.
test=develop

* NCE add selectedrows support

* NCE update weighted sampling

* fix bugs in nce_op, and assign_value_op optimized

* fix bugs in nce_op, revert assign_value_op

* nce_op optimize

* nce_op optimize

* nce_op optimize

* add selectedRows test later

test=develop

* add selectedRows supported

* add selectedRows supported

test=develop

* add selectedRows supported

* add nce selectedRows supported, test=develop

* add nce selectedRows supported

* add nce selectedRows supported, test=develop

* fix height in nce, test=develop

* add ut

* add ut, test=develop

* make AutoGrownIndex inline
test=develop

* fix tinny error, test=develop

* Fix truncated normal.

* Fix.

* Make nce support more distribution.

* Fix API.spec.

* Fix python API.

* Fix.
test=develop

* Fix API.spec
test=develop

* Fix sampler.

* Fix order of arguments in python API.
test=develop

Currently, our tests run with 2 GPUs, the init time is absurdly long:
about 4s for each process.  Currently, we run each OP test on
different processes. This PR:

1. create cmake function py_test_modules which will generate the
Makefile that runs a list of Python unittest module in a single Python
process.

2. move all "python unittest compatible" (e.g., used the unittest
package, not just a regular python file). from fluid/tests to
fluid/tests/unittests.

3. cmake now will run all OP tests in fluid/tests/unittests in a
single process, except the time-consuming tests, they are separated
into different processes to utilize parallelism. Please make sure to
use the unittest package if you put the python test file in
fluid/tests/unittests

4. remove all exit(0) from fluid/tests/unittests/*.py, exit(0) is used
to disable unittest, we can not do it when running all tests in a
single process since it will terminate the process without running the
other tests. Instead, the test is disabled in
fluid/tests/unittests/CMakeLists.txt. FIXME is added for each disabled
item. Please disable the unittest from
fluid/tests/unittests/CMakeLists.txt, instead of adding exit(0) to the
Python file, for all Python file in fluid/tests/unittests/.

5. add an option WITH_FAST_BUNDLE_TEST. When OFF, will run the unit
tests in separate process so that they can be tested individually.

* limit variable type to lod tensor in memory optimization transpiler

* refine policy

* support while operator

* fix random seed and training data order

* refine get_cfgs method to support multi while operators

* refine codes

* "fix decode bug"

* "follow commnet"

* "fix error"

* "fix hook bug"

* fix based comment

* fix copyright

* fix based on comment

* add copyright hook

* add copyright hook

* refine copyright hook

* "test copyright hook"

* fix check style

* fix ci

1. Remove checking for num_neg_samples.
2. Fix dims of Output(Cost) and Input(Bias).
3. Renamed num_sampled_classes to num_neg_samples.
4. Add TODO for add more distribution sampler.
5. Init grad_data of bias by zero.
6. Refine comments.
7. Register a kernel for type double.