* test=develop
update API.spec with hash, resolve conflict

* remove unused parameter

* optimize lstmp and sample_logits op, test=develop

* update op_use_default_grad_op_maker.spec, test=develop

* delete useless file,test=develop

* append 0 to dim variable to avoid memory reusage, test=develop

* test=develop, fix hsigmoid dereference nullptr

* test=develop, refine condition

* test=develop, refine comments

test=develop

* enable recurrent op test=develop

test=develop

test=develop

test=develop

* fix some comments, include cosine_decay,l2_normalize,pixel_shuffle

* Add api.spec, test=develop

* update api.spec, test=develop

* add api.spec,test=develop

* test=develop

* test=develop

* fix conflict,test=develop

test=develop

* add pixel_shuffle op

* add pixel_shuffle op, test=develop

* rewrite code, test=develop

* delete useless comment, test=develop

* Refine pixel_shuffle_op and unit testing

* refine code,test=develop

* refine .cu,test=develop

* fix unittest,test=develop

* Fix unit testing
test=develop

* resolve conflict, test=develop

* fix test, test=develop

* fix API, test=develop

* fix test datatype bug,test=develop

* polish comments,test=develop

* add API,test=develop

* test=develop

* Add Pixel_Shuffle OP,test=develop

* support python3,test=develop

* add include memory to travis CI bug,test=develop

test=develop

* Add linear learning warmup method

This warmup lr can be combinated with other learning rate strategies.
For example:
            decayed_lr = fluid.layers.linear_lr_warmup(
                fluid.layers.piecewise_decay(boundaries, lr_steps),
                warmup_steps, start_lr, end_lr)

test=develop

test=develop

add rank op

add rsqrt op

test=develop

* test=develop, fix space_to_depth_doc

* test=develop, refine indent

* test=develop, refine code

* test=develop, add api spec

add zeros_like op

test=develop

test=develop