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Java后端如何用DJL+TorchScript部署PyTorch图像分类模型
本文详解如何在Java后端使用DJL框架加载TorchScript导出的PyTorch图像分类模型,涵盖模型导出规范(冻结BN、替换Dropout、封装预处理)、DJL环境配置(Maven依赖、JVM内存调优、模型预热)、线程安全推理实践、Spring Boot服务集成及性能压测。强调TorchScript作为Java侧唯一安全加载通道的优势,并规避ONNX ...
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