Also, change the `labels` to `label` for api consistency

* Unify fluid submodules to fluid module

Change books just use `import fluid`, not submodules

* Remove g_main_program/g_startup_program

Use default_main_program/default_startup_program instead

* Typo

* Add API for switch default program

* Two functions: switch_main_program/switch_startup_program
* A guard: program_guard. Users can use the `with` statement change
  default programs
* Change unittests in `test_layers`

* Fix CI

* Fix CI

* Fix CI

* fix python gflags init

* format code

* Make param_attr as a strong typed class

Fix #5819

* Adding log loss operator

* Removing comments

* batch norm support matrix input

* update gpu code

* format code

* Add Python wrap of conv2d_transpose and its unittest

* Follow comments

* Fix format

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.

* Unify fluid submodules to fluid module

Change books just use `import fluid`, not submodules

* Remove g_main_program/g_startup_program

Use default_main_program/default_startup_program instead

* Typo

* Fix CI

* Restore the param infos in Program.clone()

The Program.clone only clone the variables and ops
in the program into a new program. However, the
information of Parameter is not clone.

So we need restore the information of Parameters.

Fix #5871

* Follow comments

* Fix CI

* Fix CI

* Fix CI

* py_test support argument, test_image_classification_train support argument

* use REMOVE_ITEM to rm item from list in cmake

Change books just use `import fluid`, not submodules

* conv cudnn 3d

* update test case

* update

* update

* follow comments and remove groups from helper

* update

* refine

* update

* follow comments2

* update

* fix compile

* "add asnumpy interface"

* Just for unittest

* Change unittests for numpy I/O

* Fix CI

* Stash

* Stash

* Polish Evaluator

* Merge code

* Revert

* "add floor, ceil, round op"

* "reuse zero gradient"

* "fix divide zero"

* "fix numpy floor error"

* "make global tensor function independently"

* "replace functor"

* "fix inline template error"

* "fix tensor array with CopyFrom"

* "fix other case use CopyFrom"

* "move the op interface hardly"

* "fix operators"

* "fix typo"

* "delete dynamic recurrent rnn and fix gru_unit in debugmode"

* "fix unique_ptr copy"

* "fix cuda copy"

* "fix namespace error"

* "removed nccl python test"

* "fix include error"

* "fix typo"

* fix copy util test

* beam_search_decode support multi data type

* add VisitDataType for beam search decode

* use Specialization to handle bool

* move Specialization of BeamSearchDecodeFunctor out of class

* is_training to is_test in dropout op

* handle dropout and batch_norm operator when prune pdesc in testing mode

* handle dropout and batch_norm operator when prune pdesc in testing mode

* add get_inference_program method

* fix dropout op

* fix ci

* test data after each batch training

* refine code

* refine test_book3

* fix ci

* follow comments

* Change all `data_type` in Python to `dtype`

* Change `date_type` in C++ to `dtype`

* Refine

* Adding the FTRL optimizer

* Fixed the python test case