Comments (4)
感谢您对 MegEngine 项目的关注,我们暂时没有提供 onnx 模型到 MegEngine 的转换,后续版本会添加不同平台之间的相互转换,也欢迎您参与到我们的开发中来,一起改进 MegEngine :)
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欢迎使用 https://github.com/MegEngine/mgeconvert
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@zxytim 这并不是同一件事情,MegEngine to ONNX 会近期内提供;但 ONNX to MegEngine 是独立的另外一件事情,从一个图转换到动态代码将会是一件非常困难的事情:pytorch/pytorch#21683
至于 ONNX to MegEngine 静态 graph,这个暂时不在开发计划内
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很希望有这个功能,这样能打通 pytorch 训练 --> pytorch 模型导出 onnx --> onnx 导入 megengine --> 部署 的道路
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Related Issues (20)
- [BUG Issue] DTR功能中的 eviction_threshold 这个接口是否已经失效? HOT 14
- Tensorrt execute inferences with cuda multi-streams HOT 1
- Tensor创建部分的 “是否是设备的锁页内存” 是否有误? HOT 3
- 自定义算子头文件目录 HOT 2
- Help-wanted Issue: 使用CUDA编译MegEngine后, 在GPU上的tensor的get_memory_ptr返回的指针无法直接操作,而需要通过CUDA接口操作 HOT 3
- MegEngine v1.11.0 release中的conv2d性能优化 HOT 1
- 如何针对部分Tensor值进行修改操作 HOT 2
- python 3.10 pip download wanted HOT 4
- DeformableConv2d 的 python 接口不完整 HOT 2
- 关于MegEngine/dnn/src/cuda/conv_bias/matmul/inplace_matmul_impl.cu中的代码问题 HOT 4
- AssertionError: Loss explosion: inf HOT 2
- 编译模型的时候出现error: failed to legalize operation 'MGB.ConvBias'
- NVIDIA GeForce RTX 3080(gpu0) with CUDA capability sm_86 is not compatible with the current MegEngine installation HOT 1
- Help-wanted Issue HOT 1
- RuntimeError: assertion `depth < context.transformations.size()' HOT 3
- error when run inference HOT 2
- topk_fp16 结果错误 HOT 3
- Linux下源码编译失败, 报错 /usr/bin/ld.gold: error: cannot find -lMKL_CORE_LIBRARY-NOTFOUND HOT 2
- 如何测试自定义的带 CUDA 后端的算子 HOT 7
- 将.tm模型量化成int8模型
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