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.gitattributes
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="utf-8">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>Generative Models and GANs - Slidev</title>
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<link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Inter:wght@200;400;600&family=Source+Serif+4:wght@200;400;600&family=JetBrains+Mono:wght@200;400;600&display=swap" type="text/css">
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<meta property="slidev:version" content="52.19.0">
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<meta name="description" content=""PGR207 Deep Learning 2026 — Lecture 07"">
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<meta name="author" content=""Vajira Thambawita"">
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<meta property="og:title" content="Generative Models and GANs - Slidev">
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<meta property="og:description" content=""PGR207 Deep Learning 2026 — Lecture 07""> <script type="module" crossorigin src="./assets/index-DYEUBAok.js"></script>
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./* ./index.html 200
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import{$ as e,S as t,St as n,V as r,_ as i,b as a,g as o,m as s,ut as c,v as l,vt as u,w as d,y as f,z as p}from"./modules/shiki-CkJq9tSf.js";import{t as m}from"./_plugin-vue_export-helper-BDNMzG2s.js";import{n as h}from"./slidev/context-DnYiQGy6.js";import{D as g,O as ee,S as _,a as v,h as y,i as b,n as x}from"./useGenerative-DDHg2gzY.js";import{t as S}from"./Slider-Bf0ITYx4.js";var C={class:`dl-gan`,viewBox:`0 0 470 216`,role:`img`,"aria-label":`Real and generated probability on three modes, with the optimal discriminator under each`},te=[`x1`],ne=[`x`,`y`],w=[`x`,`y`],T=[`x`,`y`,`height`],E=[`x`,`y`],D=[`x`,`y`,`height`],O=[`x`,`y`],k=[`x`,`y`],A=[`x`,`y`],j={key:0,class:`dl-gan__out`},M={class:`dl-gan__row`},N={class:`dl-gan__num`},P={class:`dl-gan__row`},F={class:`dl-gan__num`},I={class:`dl-gan__row is-quiet`},L={class:`dl-gan__num`},R={class:`dl-gan__note`},z={key:1,class:`dl-gan__out`},B=42,V=132,H=150,U=58,W=m(d({__name:`AdversarialGame`,props:{discriminatorOnly:{type:Boolean,default:!1},collapsed:{type:Boolean,default:!1}},setup(d){let{$slidev:m,$nav:W,$clicksContext:re,$clicks:ie,$page:ae,$renderContext:oe,$frontmatter:se}=h(),G=d,K=c([...G.collapsed?b:v]),q=o(()=>y(K.value)),J=o(()=>_(x,q.value)),Y=o(()=>Math.abs(J.value.v-J.value.vTheory)<5e-6);function X(e){return Math.max(e*V*(1/.62),0)}function Z(e){return U+e*136}function Q(e){K.value=[...e]}function $(e,t=3){return Number.isFinite(e)?e.toFixed(t):`∞`}return(o,c)=>{let d=S,m=g,h=ee;return p(),l(h,{"max-width":`46rem`},{controls:e(()=>[t(d,{modelValue:K.value[0],"onUpdate:modelValue":c[0]||=e=>K.value[0]=e,label:`Q on mode 1`,min:0,max:1,step:.01},null,8,[`modelValue`]),t(d,{modelValue:K.value[1],"onUpdate:modelValue":c[1]||=e=>K.value[1]=e,label:`Q on mode 2`,min:0,max:1,step:.01},null,8,[`modelValue`]),t(d,{modelValue:K.value[2],"onUpdate:modelValue":c[2]||=e=>K.value[2]=e,label:`Q on mode 3`,min:0,max:1,step:.01},null,8,[`modelValue`]),t(m,{label:`Reset`,variant:`ghost`,onClick:c[3]||=e=>Q(u(v))}),t(m,{label:`Collapse`,variant:`ghost`,onClick:c[4]||=e=>Q(u(b))}),t(m,{label:`Perfect`,variant:`ghost`,onClick:c[5]||=e=>Q(u(x))})]),readout:e(()=>[G.discriminatorOnly?(p(),a(`div`,z,[...c[10]||=[i(`div`,{class:`dl-gan__row is-quiet`},[i(`span`,{class:`dl-gan__name`},`D* = P / (P + Q)`),i(`span`,{class:`dl-gan__note`},` nothing here was trained — this is the best any discriminator could do `)],-1)]])):(p(),a(`div`,j,[i(`div`,M,[c[7]||=i(`span`,{class:`dl-gan__name`},`V(D*, G)`,-1),i(`span`,N,n($(J.value.v,5)),1)]),i(`div`,P,[c[8]||=i(`span`,{class:`dl-gan__name`},`−log 4 + 2·JS(P‖Q)`,-1),i(`span`,F,n($(J.value.vTheory,5)),1)]),i(`div`,I,[c[9]||=i(`span`,{class:`dl-gan__name`},`JS(P‖Q)`,-1),i(`span`,L,n($(J.value.js,5)),1),i(`span`,R,n(Y.value?`the two rows above are the same number, always`:``),1)])]))]),default:e(()=>[(p(),a(`svg`,C,[f(` baseline `),i(`line`,{class:`dl-gan__axis`,x1:32,x2:446,y1:H,y2:H},null,8,te),i(`text`,{class:`dl-gan__ylab`,x:26,y:22,"text-anchor":`end`},`0.6`,8,ne),i(`text`,{class:`dl-gan__ylab`,x:26,y:154,"text-anchor":`end`},`0`,8,w),(p(!0),a(s,null,r(u(x),(e,t)=>(p(),a(`g`,{key:t},[f(` the real data: an outline, because it is fixed and not yours to move `),i(`rect`,{class:`dl-gan__real`,x:Z(t),width:B,y:H-X(e),height:X(e)},null,8,T),i(`text`,{class:`dl-gan__val`,x:Z(t)+B/2,y:H-X(e)-6,"text-anchor":`middle`},n(e.toFixed(2)),9,E),f(` the generator: solid, and the only thing that moves `),i(`rect`,{class:`dl-gan__fake`,x:Z(t)+B+4,width:B,y:H-X(q.value[t]),height:X(q.value[t])},null,8,D),i(`text`,{class:`dl-gan__val is-fake`,x:Z(t)+B*1.5+4,y:H-X(q.value[t])-6,"text-anchor":`middle`},n(q.value[t].toFixed(2)),9,O),i(`text`,{class:`dl-gan__mode`,x:Z(t)+B+2,y:168,"text-anchor":`middle`},` mode `+n(t+1),9,k),f(` the best possible discriminator on this bin `),i(`text`,{class:`dl-gan__dstar`,x:Z(t)+B+2,y:192,"text-anchor":`middle`},` D* = `+n(J.value.d[t].toFixed(3)),9,A)]))),128)),c[6]||=i(`g`,{class:`dl-gan__key`},[i(`rect`,{class:`dl-gan__real`,x:`300`,y:`10`,width:`15`,height:`11`}),i(`text`,{x:`322`,y:`20`},`real, P`),i(`rect`,{class:`dl-gan__fake`,x:`376`,y:`10`,width:`15`,height:`11`}),i(`text`,{x:`398`,y:`20`},`generated, Q`)],-1)]))]),_:1})}}}),[[`__scopeId`,`data-v-a8c333fd`]]);export{W as t};
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.dl-gan[data-v-a8c333fd]{width:100%;height:100%;max-height:15rem;font-family:inherit}.dl-gan__axis[data-v-a8c333fd]{stroke:var(--dl-muted);stroke-width:1.5px}.dl-gan__ylab[data-v-a8c333fd],.dl-gan__key text[data-v-a8c333fd]{fill:var(--dl-muted);font-size:11px}.dl-gan__real[data-v-a8c333fd]{fill:none;stroke:var(--dl-body);stroke-width:2px;stroke-dasharray:4 3}.dl-gan__fake[data-v-a8c333fd]{fill:var(--dl-accent)}.dl-gan__val[data-v-a8c333fd]{fill:var(--dl-body);font-variant-numeric:tabular-nums;font-size:12px}.dl-gan__val.is-fake[data-v-a8c333fd]{fill:var(--dl-accent);font-weight:600}.dl-gan__mode[data-v-a8c333fd]{fill:var(--dl-body);font-size:12.5px}.dl-gan__dstar[data-v-a8c333fd]{fill:var(--dl-heading);font-variant-numeric:tabular-nums;font-size:13.5px;font-weight:600}.dl-gan__out[data-v-a8c333fd]{flex-direction:column;gap:.12rem;width:100%;display:flex}.dl-gan__row[data-v-a8c333fd]{color:var(--dl-heading);align-items:baseline;gap:.7rem;font-size:.86rem;display:flex}.dl-gan__row.is-quiet[data-v-a8c333fd]{color:var(--dl-muted);font-size:.8rem}.dl-gan__name[data-v-a8c333fd]{min-width:11.5rem}.dl-gan__num[data-v-a8c333fd]{color:var(--dl-accent);font-variant-numeric:tabular-nums;text-align:right;min-width:5rem;font-weight:700}.dl-gan__note[data-v-a8c333fd]{color:var(--dl-muted);font-size:.78rem;font-weight:400}
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.dl-ae[data-v-f2ff8b85]{flex-direction:column;gap:.1rem;width:100%;display:flex}.dl-ae__strip[data-v-f2ff8b85]{flex:none;width:100%;height:2.6rem;font-family:inherit}.dl-ae__axis[data-v-f2ff8b85]{stroke:var(--dl-muted);stroke-width:1.2px}.dl-ae__tick[data-v-f2ff8b85]{stroke:var(--dl-body);stroke-width:1.4px}.dl-ae__probe[data-v-f2ff8b85]{stroke:var(--dl-heading);stroke-width:2.4px}.dl-ae__probe.is-hole[data-v-f2ff8b85]{stroke:var(--dl-danger)}.dl-ae__probelab[data-v-f2ff8b85]{fill:var(--dl-heading);font-variant-numeric:tabular-nums;font-size:10.5px;font-weight:600}.dl-ae__probelab.is-hole[data-v-f2ff8b85]{fill:var(--dl-danger)}.dl-ae__striplab[data-v-f2ff8b85]{fill:var(--dl-muted);font-size:12px;font-style:italic}
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