* Make cast op support bool

Also add `elemwise_sub/mul/abs/clip` layers

* Make fuild.layers as a module

* Move layers as a module

* Split layers.py into layers module

* Fix CI

* Fix CI

Also add `elemwise_sub/mul/abs/clip` layers

* "add registry interface"

* "move function to registry"

* "rename with meaningful name"

* "add exposed layers"

* "fixed based on comments"

* "remove unsed comments"

* init decoder_trainer

* can run

* fix lod

* add sharelod to cross_entropy_grad_op

* add avg_cost to fetch list

* modify learning rate

* can run

* optimie code

* add early exit

* fix print

* revert test_understand_sentiment_conv.py

* add act to fc

* Add DataFeeder

A v2 API like data feeder for book demos.
We can feed data directly from reader.

* Fix CI

* Add an unittest for while/rnn op forward

* Add unittest for raw while op backward

* Fix CI

* Complete Dynamic RNN

* add crf_decoding layer

* fix some typo

* init trunk_evaluator

* add trunk_evaluator layer

* update chunk_eval_op and test, change int32 to int64

* fix a numeric problem

* change layers.trunk_evaluator to layers.trunk_eval

* fix typo

* add precision_val

* add crf_decoding layer

* fix some typo

* fix test_crf_decoding_op

* Add DataFeeder

A v2 API like data feeder for book demos.
We can feed data directly from reader.

* Fix CI

* Add an unittest for while/rnn op forward

* Add unittest for raw while op backward

* Fix CI

* add doc config for fluid

* fix typo

* follow comments

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

* Make param_attr as a strong typed class

Fix #5819

* Add Python wrap of conv2d_transpose and its unittest

* Follow comments

* Fix format

* 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

Change books just use `import fluid`, not submodules

* Stash

* Stash

* Polish Evaluator

* Merge code

* Revert

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

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

* Refine

* init label_semantic_roles.py

* add linear_chain_crf and test

* complete test_linear_chain_crf

* correct last layer of db_lstm

* update optimizer and initializer

* update param_initializer of embedding_layer

* support load pre trained embedding

* rm unused parameter

* optimize code

* clean code

* fix test

* add todo

* Forward of raw if-else op

* add backward part of mnist if-else unittest

* refine fill_constant_batch_size_like layer

* add draft ifelse operator

* Complete IfElse Op

* add unittest of ifelse api

* merge baidu/develop

* Stash

* Merge develop branch

* Support int/int64 for fill_constant_batch_size_like

* Improve the initializer Interface for fc, sequence_conv and conv2d layers
* Fix some typos in python code
* Fix CI

The size of the bias parameter should be the number of filters.

* init commit

* change some dir name

* fix lod_tensor_array

* init test beam search decode op

* add test_beam_search_decode_op

* Conditional Block Forward

* Assign Operator.

Out=X, when type in [LoDTensor/SelectedRows/LoDTensorArray]

* Stash

* Add Scope::Rename

it is useful in gradient phase of an operator with block

* ConditionalBlock Grad Done

* Add comments

* yapf format code

* add split lod tensor operator

* add more test cast

* clean code

* add merge lod tensor operator

* fix bug

* clean code

* add grad operator

* make mask support GPU

* add comments

* add lstm layer

* set hidden shape

* rename input parameter

* add dynamic lstm

* refine dynamic lstm layer

* change parameter using XavierInitializer by default

* refine dynamic lstm layer

* first commit

* Python API for while op

* Python Unittest for simple while_op forward

* fix out to be list

* Fix UT

* VarType

* Fix several bugs

* Fix bug

* Fix bug

* Fix Bug

* Fix bug

* Fix unittest

* Remove debug log

* Add comments

* add PADDLE_ENFORCE

* while_grad_op first commit

* Add `BlockDescBind::FindRecursiveOrCreateVar()` and fix bugs

* refine code

* fix unittest bug

* Adding operator assignment

* Adding documentation to layers.py

* Removing file from another PR