Comments (1)
No, I don't think that's gonna work because the model cannot go through torch.jit.trace
after applying int16 quantization.
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Related Issues (20)
- Whether to support pytorch to keras HOT 1
- TransposeConv wrong shape? HOT 15
- change input to INT8 after converting to tflite HOT 2
- [converter] implement torch's `aten::scaled_dot_product_attention` operator HOT 2
- Request: clamp would be more efficient to go to Bounded Relu than Maximum + Minimum HOT 3
- Do not support PReLU module? HOT 5
- torch.max not working HOT 2
- OneShotChannelPruner results in the miss of some operators HOT 4
- KeyError when executing quantization HOT 5
- PyTorch 转 TFLite 使用 int8 量化 HOT 4
- jit.trace succeed but tinynn tracer failed HOT 1
- It became larger after converting to tflite model HOT 4
- how to do Post-training integer quantization with int16 activation HOT 4
- unnecessary float() variables cause quantization to fail. HOT 7
- aten::index nodes take multiple indices in PyTorch model but cause an error when trying to convert to TFLite HOT 1
- aten::repeat_interleave is considered an unsupported Tensor and causing an error when trying to convert to TFLite HOT 2
- convert model error HOT 5
- 请问下 转tflite 模型能支持签名吗? HOT 9
- [PTQ Converter] 'Linear+relu' module conversion failed HOT 9
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