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zU*y9ipaJ@h#^6abBnh4aKV*@VftU|KL)URlX+}uOKulo3T8{=S-2(Q%yqdDw)S5nz QISfGH>FVdQ&MBb@0G{+}_W%F@ diff --git a/docs/zh_cn/tutorials/quant/post_training_quantization.md b/docs/zh_cn/tutorials/quant/post_training_quantization.md index 1e3ac3af..41b4a961 100755 --- a/docs/zh_cn/tutorials/quant/post_training_quantization.md +++ b/docs/zh_cn/tutorials/quant/post_training_quantization.md @@ -22,13 +22,13 @@ s=\frac{2^{b-1}-1}{\alpha} $$ $$ -x_{q}=\operatorname{quantize}(x, b, s)=\operatorname{clip}\left(\operatorname{round}(s \cdot x),-2^{b-1}+1,2^{b-1}-1\right) +x_{q}=\operatorname{quantize}(x, b, s)=\operatorname{clip}\left(\operatorname{round}(s \cdot x),-2^{b-1},2^{b-1}-1\right) $$ 反量化过程可以用以下公式表述: $$ -x_{q}=\operatorname{quantize}(x, b, s)=\operatorname{clip}\left(\operatorname{round}(s \cdot x),-2^{b-1}+1,2^{b-1}-1\right) +x_{dq}=\operatorname{dequantize}(x, s)=\frac{x}{s} $$ 其中,s为所选取的scale值,即将s作为尺度因子,将全精度参数映射到低比特取值范围;α为选定的全精度参数的表示范围,即全精度参数将被限制在[-α,α]内;b为量化的比特数,x为待量化的全精度参数。因此,如果给定量化的比特数b,我们只需要选定合适的α值,就可以确定量化所需的参数s。 -- GitLab