* 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

* 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 DecoupledWeightDecay

test=develop

test=develop

test=develop

test=develop

test=develop

* test=develop, fix space_to_depth_doc

* test=develop, refine indent

* test=develop, refine code

* test=develop, add api spec

* test=develop, add install check

* test=develop, add install check scripts

* test=develop, refine language

* test=develop, add api spec

* test=develop, change cdn to bj to pass ci

* Add fsp operator.
1 Add unitest.
2. Add python API.
3. Add layer test.

* Add quantization strategy.
1. Add API.
2. Add unitest.

* Add distillatoin strategy.

* Add unitest config file for quantization

* Fix Copyright
test=develop

* Fix setup.py

* Fix document of layers.py.
test=develop

* Fix unitest in python3.
test=develop

* Fix documents.
test=develop

* 1. refine fsp op by batched gemm
2. remove unused import
test=develop

* Fix test_dist_se_resnext.
1. disable test distillation.
2. reset framework.py
test=develop

* Enable unitest of distillation after fixing Block._clone_variable
test=develop

* Fix cdn issue.
test=develop

* First pr of paddle slim.
1. Add framework of paddle slim
2. Add filter pruning strategy
test=develop

* Rename unitest to tests.
test=develop

* Add prettytable into requirements.
test=develop

* Change in_nodes and out_nodes to odered dict.
test=develop

* Remove distillation.
test=develop

* Fix API.spec
test=develop

* Fix unitest.
test=develop

* Fix unitest in windows.
test=develop

* Fix unitest in windows.
test=develop

* Fix unitest.
test=develop

* Hide some functions.
test=develop

* Fix python import in python3.5
test=develop

* Fix compress pass.
test=develop

* Fix unitest of test_dist_ctr.
test=develop

* Enhence flops.

* use os.path.join

* Fix pickle for python3
Fix log and comments.
test=develop

* 1. Remove feed_reader in compress pass
2. Fix cache reader
3. Rename CompressPass to Compressor
4. Add comments for distiller optimizer
5. Remove unused pruner currently
6. Add some comments.
7. Change API.spec
test=develop

* Fix pruning in python3.
test=develop

* Fix unitest in python3.
test=develop

* Fix format in python3.
test=develop

* Add range op.
test=develop

* Add more unitests.
test=develop

* Fix API.spec
test=develop

* Fix API.spec
test=develop

* Fix API.spec
test=develop

* Rewrite gradient ProtoMaker for affine_channel_op to remove the Output as the input.
* Add act in Python API to make the act can be in-place by layer_help.py

* save infer model bug fix, return target vars' name list

test=develop

* Make step_input support custom lod level.
test=develop

* Fix API.spec
test=develop

* Fix API.spec.
test=develop

* Fix API.spec
test=develop

* Add default value in document of step_input.
test=develop

* Fix document.
test=develop

* Fix API.spec
test=develop

test=develop

test=develop

test=develop

* update load persistables for increment, test=develop

* update load persistables for increment, test=develop

* update API Spec, test=develop

* update API Spec, test=develop

* add doc, test=develop

* add doc, test=develop

* Update lookup_table_utils.py

* Update API.spec

* Update lookup_table_utils.py

test=develop

* Update API.spec

test=develop

* fix api spec

* Update lookup_table_utils.py

test=develop

test=develop

* Add moving average absmax op in quantilize-aware training.

* Support Sync Batch Norm.
* Note, do not enable it in one device.

Usage:

build_strategy = fluid.BuildStrategy()
build_strategy.sync_batch_norm = True
binary = fluid.compiler.CompiledProgram(tp).with_data_parallel(
        loss_name=loss_mean.name,
        build_strategy=build_strategy)