Refactor SequentialRecommender and add Sequential models: SASRec, BERT4Rec, GPT2Rec, FPMC

[hieuddo]

Description

• Refactor NextItemRecommender to SequentialRecommender with two settings: session-based and session-aware.
• Rename NextItemEvaluation to SequentialEvaluation
• Add new sequential models: SASRec, BERT4Rec, GPT2Rec (similar to BERT4Rec, but with GPT2 architecture)
• Refactor existing GRU4Rec compatible with session-aware setting

Quick run with 10 epochs from examples/sequential_diginetica.py:

Model	AUC	MRR	NDCG@10	NDCG@50	Recall@10	Recall@50	Train (s)	Test (s)
FPMC-sbr	0.7579	0.1254	0.1430	0.1686	0.2242	0.3398	2.8742	0.4422
GRU4Rec-sbr	0.8051	0.0611	0.0632	0.1035	0.1068	0.2907	6.0934	0.7539
SASRec-sbr	0.7902	0.3884	0.4216	0.4295	0.5289	0.5657	2.2551	1.4375
BERT4Rec-sbr	0.7880	0.3812	0.4140	0.4221	0.5201	0.5569	6.3330	1.4493
GPT2Rec-sbr	0.8111	0.3702	0.4021	0.4139	0.5096	0.5604	1.3811	1.4056
FPMC-sar	0.7480	0.1195	0.1341	0.1614	0.2067	0.3275	0.3568	0.3948
GRU4Rec-sar	0.8029	0.0754	0.0820	0.1146	0.1349	0.2837	3.4652	1.9199
SASRec-sar	0.7890	0.3891	0.4208	0.4297	0.5236	0.5639	1.6576	1.3925
BERT4Rec-sar	0.7910	0.3768	0.4080	0.4184	0.5114	0.5552	1.4889	1.3984
GPT2Rec-sar	0.8243	0.3790	0.4084	0.4217	0.5079	0.5674	1.3703	1.3644

Related Issues

Checklist:

• I have added tests.
• I have updated README.md (if you are adding a new model).
• I have updated examples/README.md (if you are adding a new example).

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[qtuantruong]

holy moly, really long PR

[hieuddo]

holy moly, really long PR

Haha. Most of these are from https://github.com/PreferredAI/CoVE/tree/main/models in our joint work with @lthoang