* - Reusing of reuder used in elementwise_add_mkldnn

- Added MKL-DNN sum prim reusing

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- Compilation fixes

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- Yet another compilation fix

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- Yet another compilation fix

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- Yet another linking fix

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- Final compilation fix

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- lint fixes

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- Lint fixes

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* - Fixes after review

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* Simplify multi_box_head API in detection.py and remove assign op.

* refine cuda place error msg, test=develop

* use LOG(ERROR)+exit(-1), test=develop

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* Update lamb optimizer

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* Regenerate api spec

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Socket can't be pickled.
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* fix softrelu doc

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* update API doc

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* test=develop, add_install_check_for_multigpu

* test=develop, refine code to use cuda_devices

* sequnce mask support max length tensor input; test=develop

* add rnn_impl.py; test=develop

* add basic gru lstm unittest; test=develop

* fix api spec; test=develop

* fix sequence_mask op bug;
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* change +-*x to elmentwise_op; test=develop

* add mkl flag; test=develop

* fix rnn impl bug; test=develop

* update api spec; test=develop

* fix doc bug; test=develop

* fix lstm bugs; test=develop

* Revert "Add multi gpu install check (#18229)"

This reverts commit 61ed06b2.

* test=develop, start ci

* optimize communicator merge sparse gradient test=develop

* revert multithread selected rows merge add test=develop

* follow comment test=develop

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* fix default value of fluid.memory_optimize
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* fix api.spec
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* Use TensorCopySync for sequence_unpad op

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* Fix the tensor memory alloc bug

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* clean build_strategy
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* DataBalanceOpHandle has been removed
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* debug

* update build_strategy.
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add Dygraph api to api.spec

* improve doc of lstm, sequence_enumerate, softmax_with_cross_entropy, space_to_depth APIs, test=develop

* update API.spec, test=develop

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* fix paddle cloud role maker bug

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* refine core cmake warning and print more info

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* fix comments

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refine StaticRNN api doc
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1. fix the bug that out_put_var in SaveSelectedRows would be empty string
2. use merge_sparse_lookup_table to replace sum op for load_persistables_for_inference
3. fix the bug in _clone_var_in_block_ when the var is SELECTED_ROWS.

(1) use channel instead of vector/BlockingQueue in Dataset，to keep same with existing implementation, and make code more readable and flexible (dataset single output channel or multi output channel). one previous memory out of limit problem is cause by not release memory after training.
(2) add Record because MultiSlotType costs too much memory (80B)，fix memory out of limit problem.
(3) add Channel, Archive in paddle/fluid/framework
(4) change dataset from shared_ptr to unique_ptr in pybind
(5) move create/destroy readers from trainer to dataset
(6) move shuffle from datafeed to dataset. dataset holds memory, datafeed is only for load data and feed data to network.
(7) fix thread num bug of Dataset when filelist size < thread num
(8) support set_queue_num in InMemoryDataset

* improve the doc of DataFeeder and default_main_program

* update API.spec, test=develop