Comments (1)
Duplicate of #4. The integration with FX is not our top priority at present, but we will look into it at a reasonable time in the future.
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Related Issues (20)
- Meet Detailed error: Tensor-likes are not close! using TFLiteConverter HOT 2
- [Converter] Need transpose optimization HOT 2
- Float model failed to convert to TFLite
- [converter] map gather(+reshape) ops with seperate consecutive indices to split(unpack) ops
- tinynn.converter module not found! HOT 2
- [CI] several tests for modifier failed
- 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
- Does tinynn support following int16 quantization? HOT 1
- 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
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