Comments (2)
WebDNN supports ONNX.
Actually, PyTorch converter is implemented by parsing exported ONNX model.
https://github.com/mil-tokyo/webdnn/tree/master/src/graph_transpiler/webdnn/frontend/onnx
I have not tested ONNX exported by Chainer, but it theorethically works.
As more frameworks are supporting ONNX, we will focus ONNX as primary input format in the future.
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thanks @milhidaka - this is cool to see. Let me know if you'd like to be showcased as an ONNX project on onnx.ai. If so, send me a email at [email protected] and we can add your logo, etc..
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Related Issues (20)
- Implement ONNX BatchNormalization
- Avoid memory error on default
- Update emscripten setup instruction
- how long will it support pytorch 1.0? HOT 2
- Does this run at all on Edge? HOT 3
- Question about writing my OPS HOT 4
- WebGL2 Compute shader support? HOT 2
- OpenNSFW caffe model always returns the same output HOT 3
- Support WebMetal HOT 1
- Support Chainer 5.x
- Full rename of WebGPU -> WebMetal
- obtain python framework model from webdnn HOT 1
- Does not work on iOS Safari without WebMetal enabled HOT 1
- How to use a TensorFlow 1.13.0 model with WebDNN?
- Support removal of Module.buffer in emscripten
- "Gather" operator not implemented yet error HOT 2
- What the model is HOT 5
- error in webdnn setup command: "values of 'package_data' dict" must be a list of strings (got '*.js')
- Any one could explain the differences between "WebGL via Metal" vs. "WebGPU" on iOS? HOT 2
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