Showing 2 open source projects for "fb2k-component"

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    OnnxStream

    OnnxStream

    Lightweight inference library for ONNX files, written in C++

    ...So I decided to write a super small and hackable inference library specifically focused on minimizing memory consumption: OnnxStream. OnnxStream is based on the idea of decoupling the inference engine from the component responsible for providing the model weights, which is a class derived from WeightsProvider. A WeightsProvider specialization can implement any type of loading, caching, and prefetching of the model parameters.
    Downloads: 8 This Week
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    SSD in PyTorch 1.0

    SSD in PyTorch 1.0

    High quality, fast, modular reference implementation of SSD in PyTorch

    ...Multi-GPU training and inference: We use DistributedDataParallel, you can train or test with arbitrary GPU(s), the training schema will change accordingly. Add your own modules without pain. We abstract backbone, Detector, BoxHead, BoxPredictor, etc. You can replace every component with your own code without changing the code base. For example, You can add EfficientNet as the backbone, just add efficient_net.py (ALREADY ADDED) and register it, specific it in the config file, It's done! Smooth and enjoyable training procedure: we save the state of model, optimizer, scheduler, training iter, you can stop your training and resume training exactly from the save point without change your training CMD.
    Downloads: 0 This Week
    Last Update:
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