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- FP16 training for memory saving and up to **2.5X** acceleration
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- Highly scalable distributed training available **out of box**
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- Full coverage of state-of-the-art models including FasterRCNN, MaskRCNN, CascadeRCNN, RetinaNet, [DCNv1/v2](./models/dcn), **[TridentNet](./models/tridentnet)**, **[NASFPN](./models/NASFPN)** , **[EfficientNet](./models/efficientnet)**, and **[Kownledge Distillation](./models/KD)**
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- Full coverage of state-of-the-art models including FasterRCNN, MaskRCNN, CascadeRCNN, RetinaNet, [DCNv1/v2](./models/dcn), **[TridentNet](./models/tridentnet)**, **[NASFPN](./models/NASFPN)** , **[EfficientNet](./models/efficientnet)**, and **[Knowledge Distillation](./models/KD)**
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- Extensive feature set including **large batch BN**, **loss synchronization**, **automatic BN fusion**, soft NMS, multi-scale train/test
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- Modular design for coding-free exploration of new experiment settings
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- Extensive documentations including [annotated config](./doc/fully_annotated_config.py), [Fintuning Guide](./doc/FINETUNE.md)
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