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Replace \bm with \bf
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chapter_model_deployment/Conversion_to_Inference_Model_and_Model_Optimization.md

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@@ -90,7 +90,7 @@ understood as the simplification of an equation. The computation of
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Convolution is expressed as Equation
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:eqref:`ch-deploy/conv-equation`.
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$$\bm{Y_{\rm conv}}=\bm{W_{\rm conv}}\cdot\bm{X_{\rm conv}}+\bm{B_{\rm conv}}$$
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$$\bf{Y_{\rm conv}}=\bf{W_{\rm conv}}\cdot\bf{X_{\rm conv}}+\bf{B_{\rm conv}}$$
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:eqlabel:`equ:ch-deploy/conv-equation`
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Here, we do not need to understand what each variable means. Instead, we
@@ -103,7 +103,7 @@ Equation
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:eqref:`ch-deploy/bn-equation` is about the computation of
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Batchnorm:
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$$\bm{Y_{\rm bn}}=\gamma\frac{\bm{X_{\rm bn}}-\mu_{\mathcal{B}}}{\sqrt{{\sigma_{\mathcal{B}}}^{2}+\epsilon}}+\beta$$
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$$\bf{Y_{\rm bn}}=\gamma\frac{\bf{X_{\rm bn}}-\mu_{\mathcal{B}}}{\sqrt{{\sigma_{\mathcal{B}}}^{2}+\epsilon}}+\beta$$
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:eqlabel:`equ:ch-deploy/bn-equation`
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Similarly, it is an equation for $\bm{Y_{\rm bn}}$ with respect to
@@ -117,7 +117,7 @@ After substituting $\bm{Y_{\rm conv}}$ into $\bm{X_{\rm bn}}$ and
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uniting and extracting the constants, we obtain Equation
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:eqref:`ch-deploy/conv-bn-equation-3`.
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$$\bm{Y_{\rm bn}}=\bm{A}\cdot\bm{X_{\rm conv}}+\bm{B}$$
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$$\bf{Y_{\rm bn}}=\bf{A}\cdot\bf{X_{\rm conv}}+\bf{B}$$
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:eqlabel:`equ:ch-deploy/conv-bn-equation-3`
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Here, $\bm{A}$ and $\bm{B}$ are two matrices. It can be noticed that
@@ -183,7 +183,7 @@ principle of operator replacement. After decomposing Equation
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folding the constants, Batchnorm is defined as Equation
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:eqref:`ch-deploy/replace-scale`
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$$\bm{Y_{bn}}=scale\cdot\bm{X_{bn}}+offset$$
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$$\bf{Y_{bn}}=scale\cdot\bf{X_{bn}}+offset$$
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:eqlabel:`equ:ch-deploy/replace-scale`
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where **scale** and **offsets** are scalars. This simplified formula can

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