* Addign document for fluid split_lod_tensor

* Adding document for fluid merge_lod_tensor

Adding documentation for the operators: lod_tensor_to_array , array_to_lod_tensor, create_array, increment (#6807)

* Adding operator assignment

* Adding a prototype for documentation in layers

* small update to re-run Travis

* Removing file from another PR

* Small typo

* Adding documentation for the operators: lod_tensor_to_array , array_to_lod_tensor, create_array, increment

* Fixing indentation issue

* Fixed datatype of input variables

* Writeup for array write layer

* Fixed the type

It is useful to reorder RNN memory block.

* Simplize system_allocator and fix GPU_INFO

* Remove main_program/startup_program

* Fix optimizer

* Fix CI

* Follow comments

* 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