tensorflow / tensorflow/model-optimization
quantizing to int values
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Since Nov 8, 2021.
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Description
Hello,
I have used your QAT model to quantize to different bitwidths, but I saw that the quantizations were always to FP values, even if they were quantized (e.g., if I quantized to 4bit, then all my weight were quantized to 16 discrete values, but they were not integers but rather FP values, namely non-integers.
I was wondering if there is a way to perform the QAT with a quantization-technique that quantizes to integers, so at to it would be more hardware-efficient.
Thank you.
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