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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2022/11/14 15:09:52 UTC

[GitHub] [tvm] guberti commented on issue #13364: [Bug] [microTVM] Native schedules for microTVM have worse accuracy than expected

guberti commented on issue #13364:
URL: https://github.com/apache/tvm/issues/13364#issuecomment-1313903539

   # How does quantization work in general?
   
   Consider a **fused, quantized conv2d** operator, like those in the MLPerf Tiny (or any quantized MobileNetV1 model). In addition to having a kernel and bias, our operator has "three" extra parameters related to quantization (I'm simplifying slightly):
   
   - An **input zero point** (an `int32`)
   - One **requantization scale multiplier** per channel (a `float32`)
   - An **output zero point** (an `int32` that equals the input zero point for the next layer)
   - 
   
   $$3$$


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