Comments (4)
jianjunjiang
commented on May 25, 2024
see struct onnx_tensor_t, this can expressd for any data type, CUDA inference, you must write a struct onnx_resolver_t, this is a iterface for some hardware acceleration
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delldu
commented on May 25, 2024
@jianjunjiang ,Thank you. We also wonder how support dynamic input shape with libonnx ? Would you please give us some advance ?
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jianjunjiang
commented on May 25, 2024
using onnx_tensor_apply function to modify input tensor
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delldu
commented on May 25, 2024
Many thanks.
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Related Issues (20)
- 可以参考下ONNC怎么做的
- Tensorflow model with opset 12 seems to crash when loaded HOT 5
- Which header files are necessary? HOT 2
- Why does every test in the model, node and simple folders fail? HOT 2
- How to convert a `onnx_context` to a `unsigned char array` as in the hello world example? HOT 3
- Failed to load 'yolov5n.onnx'. HOT 2
- Maxpool + dilation
- Inference on GPU HOT 4
- Support GRU? HOT 1
- Valgrind output for Yolo v2 model HOT 1
- Unsupported opset => Gather-11 (ai.onnx) HOT 2
- Python bindings HOT 9
- Support ORT (flatbuffers) models
- Should Conv nodes be optimized using FFT?
- Implement Fourier transform nodes
- Evaluate if it makes sense to utilize NNPack
- 请问在哪里看opset_version和对应版本所支持的算子列表？
- compile failed , report the error which macro undefined HOT 1
- Fail to compile on macOs
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