Integrated Trainer of Parameter Server (API add `fluid.contrib.layers.sparse_embedding` only)

[seiriosPlus]

PR types

New features, Function optimization

PR changes

APIs, OPs, Others

Describe

fully optimized code for parameter server training.

Introduction

---

API changes:

1. add fluid.contrib.sparse_embedding for large sparse embedding.
2. other API changes caused by code formatter.

OP changes:

1. recv_save add attribute is_sparse
2. send remove unused attribute send
3. checkpoint_notify remove attributes trainer_id/dir/lookup_table/epmap
4. checkpoint_notify add attributes is_slice/varname/remote_varnames/endpoints/slice_varnames/dirname
5. distributed_lookup_table delete unused attribute height_sections

explain: recv_save / send / checkpoint_notify / distributed_lookup_table are all private ops for distributed training, user-friendly.

Transpiler

old: huge methods with if/for loop new: passes

trainer: delete_optimizer_pass->distributed_ops_pass->append_send_ops_pass->fake_init_ops_pass->init_from_server_pass->delet_extra_optimizes_pass pserver: add_listen_and_serv_pass->add_rpc_global_flags_pass->add_optimizer_pass->large_scale_sparse_pass->build_pserver_startup_program_pass->large_scale_sparse_pass

Communicator

reimplement: Communicator -> AsyncComunicator -> GeoCommunicator Communicator -> AsyncComunicator -> HalfAsyncCommunicator -> SyncCommunicator

Server

add LargeScaleKV implement

1. auto growth id
2. id in [0, INT64]
3. hash by pservers， fix hotspot issues.
4. save to SelectedRows/Text
5. PServer Save

---

Experiments

CTR LARGE_SCALE VS 1.7.2(8)	SPEED lines/esc			TEST AUC
ASYNC + DATASET
EPOCH	22957	1.7.2	22957	1.7.2
0	40382.7114	41824.4988	0.743417	0.747783
1	40852.5408	42742.1863	0.763407	0.765855
2	41757.7742	42824.1947	0.773173	0.775051
3	42245.0450	41419.2507	0.779447	0.780185
4	42255.9334	43046.1868	0.782906	0.783628
5	41638.7534	43064.7863	0.785447	0.785996
6	41625.8496	43903.9036	0.787759	0.787912
7	41826.0234	43849.0151	0.789067	0.789307
8	41644.1003	43084.6209	0.790005	0.790547
9	42006.6102	45298.1854	0.791332	0.791442
10	41520.9987	44090.6176	0.791979	0.792363
11	41644.4256	44754.7476	0.79242	0.792934
12	41600.1201	44129.0481	0.792934	0.793618
13	42242.2510	43911.7627	0.793653	0.793995
14	42493.9051	43280.5678	0.793839	0.794289
15	42483.4592	43156.0943	0.794197	0.794641
16	41973.2283	43050.7187	0.794247	0.794467
17	41648.6511	43470.0413	0.794318	0.795061
18	42001.9489	43878.2971	0.794401	0.794801
19	43204.9721	44350.7521	0.794796	0.794991

W2V LARGE_SCALE VS 1.7.2(8)	SPEED words/esc			TEST ACC
ASYNC + DATASET
EPOCH	22957	1.7.2	22957	1.7.2
0	38710.8308	52546.4205	0.357	0.291
1	31047.3975	53228.6121	0.488	0.421
2	38398.9667	53219.9925	0.552	0.483
3	30892.7404	52935.8162	0.592	0.53
4	38253.3532	53083.7943	0.609	0.57
5	30509.0984	52890.2298	0.614	0.583
6	36201.4896	52968.6198	0.621	0.6
7	31285.0067	53509.7486	0.628	0.608
8	34499.2948	52988.9057	0.632	0.615
9	34003.5555	53091.7894	0.634	0.62
10	32231.5232	52983.9373	0.637	0.623
11	36732.4116	52930.2642	0.64	0.63
12	29601.1020	52820.1654	0.639	0.632
13	47984.6335	53022.2126	0.64	0.634
14	44598.9333	53156.1390	0.641	0.635

SIMNET LARGE_SCALE VS 1.7.2(8)	SPEED lines/esc			TEST PN
ASYNC + DATASET
EPOCH	22957	1.7.2	22957	1.7.2
0	80882.7005	69527.7479	1.80131	1.83487
2	80851.1122	69427.2556	1.92519	1.95693
4	81212.7949	69551.4940	1.99275	2.01557
6	81046.8461	69718.6492	2.02755	2.065
8	81191.8261	69810.9468	2.0512	2.07834
10	81614.7143	69974.7245	2.08456	2.11172
12	80365.6785	69782.9580	2.06726	2.12081
14	80845.8114	70085.8516	2.1108	2.1329
16	81453.6759	70270.9776	2.12224	2.11487
18	80598.0124	70201.1548	2.14547	2.16318
20	80936.1689	69586.5245	2.12098	2.17401
22	80281.5667	69935.3969	2.16638	2.17755
24	80648.5904	69712.8900	2.17197	2.18454
26	80175.3672	69874.0455	2.17442	2.18979
28	80482.3953	69670.9059	2.1805	2.19599
30	80357.8911	69693.6987	2.18897	2.20132
32	80576.7476	69591.5745	2.19511	2.20476
34	81010.0043	69194.1689	2.19904	2.21155
36	80852.6387	69869.2369	2.19907	2.20889
38	80696.7542	69573.0540	2.2062	2.20458

NEXT Work

1. the full unification of Tensor and LargeScakeLV on PServer
2. Speed up for Geo/Async.
3. more test at business situations.

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