wuziheng 9aaa600f79 Yolox improve with REPConv/ASFF/TOOD (#154) ... * add attention layer and more loss function * add attention layer and various loss functions * add siou loss * add tah,various attention layers, and different loss functions * add asff sim, gsconv * blade utils fit faster * blade optimize for yolox static & fp16 * decode output for yolox control by cfg * add reparameterize_models for export * e2e trt_nms plugin export support and numeric test * split preprocess from end2end+blade, speedup from 17ms->7.2ms Co-authored-by: zouxinyi0625 <zouxinyi.zxy@alibaba-inc.com>		2022-08-24 18:11:15 +08:00
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__init__.py	initial commit	2022-04-02 20:01:06 +08:00
test_yolox.py	Yolox improve with REPConv/ASFF/TOOD (#154)	2022-08-24 18:11:15 +08:00