* wip

* clean up

* should fix running with memopt

* add ut

* mark lr schedule op role

* hide lr_schedule_guard

* use op_role_var instead of ufind

* unify dist test name

* wip for py3 support

* fix var deref

* fix python3 mem_opt order

* remove comments

use clone(for_test=True) replace get_inference_program

* Add roi perspective transform.

* Add roi_perspective_transform_op.

* Fix code style.

* Add python api and fix doc.

* Fix API.spec

* Fix python api.

* Fix API.spec

* Move src to detection.

convert **kwargs to explicit arguments

Disable test_fuse_elewise_add_act in mac

Fix sparse Adam and Gradient clip of SelectedRows

Add warning when disable test_fuse_elewise_add_act_pass on Mac

* refine analyzer_nlp_tester

* refine analyzer_rnn/vis_tester

add readme of /doc

* Optimize GRU with AVX instruction

* Clean code

* Add the Unitest and fix the align issue

* Remove the remanent part of the unitest part

* Code clean

* Fix the parameters length issue for fusion_gru to pass CI

* Change the default type as float32

* Add Preface

* Add demo code

* Save file

* Refine code

* seems can work

* use elementwise strategy

* Use ElementwiseComputeEx

* Add comments

* extract functions from operator

* Refine code

* Follow comment

* code refine

* add op_fuse  pass

* add backward

* code refine

* use TopologySortOperations

* follow comments

* refine IsFusible

* code enhance

* fix op_fusion_pass

* refine code

* refine fuse_elemwise_act_op

* adjust the input and output

* refine logic

* add intermediate_edge

* disable inplace

* follow comments

* refine logic

* follow comments

* Remove the removable IntermediateOut

* change strategy

* code refine

* enable fuse backward

* code refine

* code refine

* rename unit test

* follow comments

update mklml version

Also deprecate LARs argument

Delete develop doc/fluid folder

Sequence Scatter Op

To support full model saving.

fix mac unittest 279/395 error without distribute

move uci_housing dataset to bce

hidden InferenceTranspiler

avoid creating dangling ir::Node.

In the future, we'd like to encourage user to save
everything during training.
This allows us to
1. Do more flexible optimization passes
2. Re-train and fune-tune

fix mac unitest on ci

fix mac compile error

fix py2 matplotlib deps