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

* Rename unitest to tests.
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* Add prettytable into requirements.
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* Change in_nodes and out_nodes to odered dict.
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* Remove distillation.
test=develop

* Fix API.spec
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* Fix unitest.
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* Fix unitest in windows.
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* Fix unitest in windows.
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* Fix unitest.
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* Hide some functions.
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* Fix python import in python3.5
test=develop

* Fix compress pass.
test=develop

* Fix unitest of test_dist_ctr.
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* 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.
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* Fix format in python3.
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* Add range op.
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* Add more unitests.
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* Fix API.spec
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* Fix API.spec
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* Fix API.spec
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* 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

* Make step_input support custom lod level.
test=develop

* Fix API.spec
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* Fix API.spec.
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* Fix API.spec
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* Add default value in document of step_input.
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* Fix document.
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* Fix API.spec
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* 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

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* 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)

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* polish the cast op doc

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* follow comments

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* fix api.spec

test=develop

* polish the cast op doc

test=develop

* follow comments

test=develop

* fix api.spec

test=develop

* remove the ignored from is_empty and less_than test=develop

* fix api spec test=develop

* fix the api spec test=develop

* test=develop