Buckets:
| import{s as Kt,o as qt,n as Bt}from"../chunks/scheduler.f3b1e791.js";import{S as St,i as zt,e as i,s as r,c,h as Qt,a as d,d as n,b as o,f as I,g as p,j as $,k as J,l as s,m as l,n as m,t as k,o as g,p as f}from"../chunks/index.023a9934.js";import{C as Yt}from"../chunks/CopyLLMTxtMenu.c780467c.js";import{D as Z,E as Ut}from"../chunks/ExampleCodeBlock.2e41434f.js";import{C as Xt}from"../chunks/CodeBlock.fc650646.js";import{H as C,E as At}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.fb377ec3.js";function Ot(pe){let u,j="Example:",v,h,_;return h=new Xt({props:{code:"aW1wb3J0JTIwdG9yY2glMEFmcm9tJTIwa2VybmVscyUyMGltcG9ydCUyMGdldF9rZXJuZWwlMEElMEFhY3RpdmF0aW9uJTIwJTNEJTIwZ2V0X2tlcm5lbCglMjJrZXJuZWxzLWNvbW11bml0eSUyRnJlbHUlMjIlMkMlMjB2ZXJzaW9uJTNEMSklMEF4JTIwJTNEJTIwdG9yY2gucmFuZG4oMTAlMkMlMjAyMCUyQyUyMGRldmljZSUzRCUyMmN1ZGElMjIpJTBBb3V0JTIwJTNEJTIwdG9yY2guZW1wdHlfbGlrZSh4KSUwQXJlc3VsdCUyMCUzRCUyMGFjdGl2YXRpb24ucmVsdShvdXQlMkMlMjB4KQ==",highlighted:`<span class="hljs-keyword">import</span> torch | |
| <span class="hljs-keyword">from</span> kernels <span class="hljs-keyword">import</span> get_kernel | |
| activation = get_kernel(<span class="hljs-string">"kernels-community/relu"</span>, version=<span class="hljs-number">1</span>) | |
| x = torch.randn(<span class="hljs-number">10</span>, <span class="hljs-number">20</span>, device=<span class="hljs-string">"cuda"</span>) | |
| out = torch.empty_like(x) | |
| result = activation.relu(out, x)`,lang:"python",wrap:!1}}),{c(){u=i("p"),u.textContent=j,v=r(),c(h.$$.fragment)},l(a){u=d(a,"P",{"data-svelte-h":!0}),$(u)!=="svelte-11lpom8"&&(u.textContent=j),v=o(a),p(h.$$.fragment,a)},m(a,b){l(a,u,b),l(a,v,b),m(h,a,b),_=!0},p:Bt,i(a){_||(k(h.$$.fragment,a),_=!0)},o(a){g(h.$$.fragment,a),_=!1},d(a){a&&(n(u),n(v)),f(h,a)}}}function en(pe){let u,j="Example:",v,h,_;return h=new Xt({props:{code:"ZnJvbSUyMGtlcm5lbHMlMjBpbXBvcnQlMjBnZXRfa2VybmVsJTJDJTIwZ2V0X2xvYWRlZF9rZXJuZWxzJTBBJTBBZ2V0X2tlcm5lbCglMjJrZXJuZWxzLWNvbW11bml0eSUyRmFjdGl2YXRpb24lMjIlMkMlMjB2ZXJzaW9uJTNEMSklMEFmb3IlMjBsb2FkZWQlMjBpbiUyMGdldF9sb2FkZWRfa2VybmVscygpJTNBJTBBJTIwJTIwJTIwJTIwcHJpbnQobG9hZGVkLm1ldGFkYXRhLm5hbWUlMkMlMjBsb2FkZWQucmVwb19pbmZvKQ==",highlighted:`<span class="hljs-keyword">from</span> kernels <span class="hljs-keyword">import</span> get_kernel, get_loaded_kernels | |
| get_kernel(<span class="hljs-string">"kernels-community/activation"</span>, version=<span class="hljs-number">1</span>) | |
| <span class="hljs-keyword">for</span> loaded <span class="hljs-keyword">in</span> get_loaded_kernels(): | |
| <span class="hljs-built_in">print</span>(loaded.metadata.name, loaded.repo_info)`,lang:"python",wrap:!1}}),{c(){u=i("p"),u.textContent=j,v=r(),c(h.$$.fragment)},l(a){u=d(a,"P",{"data-svelte-h":!0}),$(u)!=="svelte-11lpom8"&&(u.textContent=j),v=o(a),p(h.$$.fragment,a)},m(a,b){l(a,u,b),l(a,v,b),m(h,a,b),_=!0},p:Bt,i(a){_||(k(h.$$.fragment,a),_=!0)},o(a){g(h.$$.fragment,a),_=!1},d(a){a&&(n(u),n(v)),f(h,a)}}}function tn(pe){let u,j,v,h,_,a,b,Ee,G,Pe,U,De,y,B,lt,me,wt="Load a kernel from the kernel hub.",st,ke,Ct=`This function downloads a kernel to the local Hugging Face Hub cache directory (if it was not downloaded before) | |
| and then loads the kernel.`,at,V,Re,X,Ze,P,K,it,ge,Mt="Import a kernel from a local kernel repository path.",Ve,q,Fe,D,S,dt,fe,Lt="Check whether a kernel build exists for the current environment (Torch version and compute framework).",He,z,We,M,Q,ct,ue,Nt="Resolve all build variants of a kernel against the current environment.",pt,he,It=`The decisions are sorted with compatible variants first, the most preferred | |
| variant leading.`,Ge,Y,Ue,T,A,mt,$e,Jt="Return a snapshot of every kernel that has been loaded into the current process.",kt,_e,jt="The returned list is a new list; mutating it does not affect the registry.",gt,F,Be,O,Xe,ee,Ke,L,te,ft,ve,Et="Get a pre-downloaded, locked kernel.",ut,be,Pt="If <code>lockfile</code> is not specified, the lockfile will be loaded from the caller’s package metadata.",qe,ne,Se,R,re,ht,xe,Dt="Get a kernel using a lock file.",ze,oe,Qe,le,Ye,x,se,$t,ye,Rt="This dataclass provides information about a loaded kernel:",_t,Te,Zt=`<li><code>metadata</code> (<code>Metadata</code>): kernel metadata.</li> <li><code>module</code> (<code>ModuleType</code>): the imported kernel module.</li> <li><code>repo_info</code> (<code>kernels.utils.RepoInfo | None</code>): populated only for | |
| kernels loaded via <code>get_kernel</code>. Loaders that work from a local path | |
| (<code>get_local_kernel</code>) or a lockfile (<code>get_locked_kernel</code>, <code>load_kernel</code>) | |
| leave this as <code>None</code>.</li>`,vt,we,Vt="The metadata includes the following properties that describe a kernel:",bt,Ce,Ft="<li><code>id</code> (<code>str</code>): kernel identifier that is unique to the kernel version + backend.</li> <li><code>name</code> (<code>str</code>): the name of the kernel.</li> <li><code>version</code> (<code>int</code>): the version of the kernel.</li> <li><code>license</code> (<code>str</code>): the license of the kernel.</li> <li><code>upstream</code> (<code>str | None</code>): the upstream repository of the kernel.</li> <li><code>python_depends</code> (<code>list[str]</code>): required Python dependencies.</li> <li><code>backend</code>: information about the kernel’s backend.</li>",Ae,ae,Oe,w,ie,xt,Me,Ht="This dataclass stores the origin of the kernel.",yt,Le,Wt="The following fields are available:",Tt,Ne,Gt="<li><code>repo_id</code> (<code>str</code>): the Hub repository containing the kernel.</li> <li><code>revision</code> (<code>str</code>): the specific revision of the kernel.</li>",et,de,tt,je,nt;return _=new Yt({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),b=new C({props:{title:"Kernels API Reference",local:"kernels-api-reference",headingTag:"h1"}}),G=new C({props:{title:"Main Functions",local:"main-functions",headingTag:"h2"}}),U=new C({props:{title:"get_kernel",local:"kernels.get_kernel",headingTag:"h3"}}),B=new Z({props:{name:"kernels.get_kernel",anchor:"kernels.get_kernel",parameters:[{name:"repo_id",val:": str"},{name:"revision",val:": str | None = None"},{name:"version",val:": int | None = None"},{name:"backend",val:": str | None = None"},{name:"user_agent",val:": str | dict | None = None"},{name:"trust_remote_code",val:": bool | list[str] = False"}],parametersDescription:[{anchor:"kernels.get_kernel.repo_id",description:`<strong>repo_id</strong> (<em>str</em>) — | |
| The Hub repository containing the kernel.`,name:"repo_id"},{anchor:"kernels.get_kernel.revision",description:`<strong>revision</strong> (<em>str</em>, <em>optional</em>) — | |
| The specific revision (branch, tag, or commit) to download. Cannot be used together with <em>version</em>.`,name:"revision"},{anchor:"kernels.get_kernel.version",description:`<strong>version</strong> (<em>int</em>, <em>optional</em>) — | |
| The kernel version to download. Cannot be used together with <em>revision</em>. | |
| Either <em>version</em> or <em>revision</em> must be specified.`,name:"version"},{anchor:"kernels.get_kernel.backend",description:`<strong>backend</strong> (<em>str</em>, <em>optional</em>) — | |
| The backend to load the kernel for. Can only be <em>cpu</em> or the backend that Torch is compiled for. | |
| The backend will be detected automatically if not provided.`,name:"backend"},{anchor:"kernels.get_kernel.user_agent",description:`<strong>user_agent</strong> (<em>Union[str, dict]</em>, <em>optional</em>) — | |
| The <em>user_agent</em> info to pass to <em>snapshot_download()</em> for internal telemetry.`,name:"user_agent"},{anchor:"kernels.get_kernel.trust_remote_code",description:`<strong>trust_remote_code</strong> (<em>bool | list[str]</em>, <em>optional</em>, defaults to <em>False</em>) — | |
| Whether to allow loading kernels from untrusted organisations. When <code>False</code>, | |
| only kernels from trusted organisations are allowed. When <code>True</code>, all | |
| repositories are allowed. A list of strings will be used to verify signing | |
| identities in a future release; for now it emits a warning and falls | |
| back to the default trust check.`,name:"trust_remote_code"}],source:"https://github.com/huggingface/kernels/blob/vr_607/kernels/src/kernels/utils.py#L415",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p>The imported kernel module.</p> | |
| `,returnType:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p><em>ModuleType</em></p> | |
| `}}),V=new Ut({props:{anchor:"kernels.get_kernel.example",$$slots:{default:[Ot]},$$scope:{ctx:pe}}}),X=new C({props:{title:"get_local_kernel",local:"kernels.get_local_kernel",headingTag:"h3"}}),K=new Z({props:{name:"kernels.get_local_kernel",anchor:"kernels.get_local_kernel",parameters:[{name:"repo_path",val:": Path"},{name:"backend",val:": str | None = None"}],parametersDescription:[{anchor:"kernels.get_local_kernel.repo_path",description:`<strong>repo_path</strong> (<code>Path</code>) — | |
| The local path to the kernel repository.`,name:"repo_path"},{anchor:"kernels.get_local_kernel.backend",description:`<strong>backend</strong> (<code>str</code>, <em>optional</em>) — | |
| The backend to load the kernel for. Can only be <code>cpu</code> or the backend that Torch is compiled for. | |
| The backend will be detected automatically if not provided.`,name:"backend"}],source:"https://github.com/huggingface/kernels/blob/vr_607/kernels/src/kernels/utils.py#L483",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p>The imported kernel module.</p> | |
| `,returnType:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p><code>ModuleType</code></p> | |
| `}}),q=new C({props:{title:"has_kernel",local:"kernels.has_kernel",headingTag:"h3"}}),S=new Z({props:{name:"kernels.has_kernel",anchor:"kernels.has_kernel",parameters:[{name:"repo_id",val:": str"},{name:"revision",val:": str | None = None"},{name:"version",val:": int | None = None"},{name:"backend",val:": str | None = None"}],parametersDescription:[{anchor:"kernels.has_kernel.repo_id",description:`<strong>repo_id</strong> (<code>str</code>) — | |
| The Hub repository containing the kernel.`,name:"repo_id"},{anchor:"kernels.has_kernel.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>) — | |
| The specific revision (branch, tag, or commit) to download. Cannot be used together with <code>version</code>.`,name:"revision"},{anchor:"kernels.has_kernel.version",description:`<strong>version</strong> (<code>int</code>, <em>optional</em>) — | |
| The kernel version to download. Cannot be used together with <code>revision</code>. | |
| Either <code>version</code> or <code>revision</code> must be specified.`,name:"version"},{anchor:"kernels.has_kernel.backend",description:`<strong>backend</strong> (<code>str</code>, <em>optional</em>) — | |
| The backend to load the kernel for. Can only be <code>cpu</code> or the backend that Torch is compiled for. | |
| The backend will be detected automatically if not provided.`,name:"backend"}],source:"https://github.com/huggingface/kernels/blob/vr_607/kernels/src/kernels/utils.py#L516",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p><code>True</code> if a kernel is available for the current environment.</p> | |
| `,returnType:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p><code>bool</code></p> | |
| `}}),z=new C({props:{title:"get_kernel_variants",local:"kernels.get_kernel_variants",headingTag:"h3"}}),Q=new Z({props:{name:"kernels.get_kernel_variants",anchor:"kernels.get_kernel_variants",parameters:[{name:"repo_id",val:": str"},{name:"revision",val:": str | None = None"},{name:"version",val:": int | None = None"},{name:"backend",val:": str | None = None"}],parametersDescription:[{anchor:"kernels.get_kernel_variants.repo_id",description:`<strong>repo_id</strong> (<code>str</code>) — | |
| The Hub repository containing the kernel.`,name:"repo_id"},{anchor:"kernels.get_kernel_variants.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>) — | |
| The specific revision (branch, tag, or commit) to inspect. Cannot be used together with <code>version</code>.`,name:"revision"},{anchor:"kernels.get_kernel_variants.version",description:`<strong>version</strong> (<code>int</code>, <em>optional</em>) — | |
| The kernel version to inspect. Cannot be used together with <code>revision</code>. | |
| Either <code>version</code> or <code>revision</code> must be specified.`,name:"version"},{anchor:"kernels.get_kernel_variants.backend",description:`<strong>backend</strong> (<code>str</code>, <em>optional</em>) — | |
| The backend to resolve variants for. Can only be <code>cpu</code> or the backend that Torch is compiled for. | |
| The backend will be detected automatically if not provided.`,name:"backend"}],source:"https://github.com/huggingface/kernels/blob/vr_607/kernels/src/kernels/utils.py#L557",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p>One <code>VariantAccepted</code> or <code>VariantRejected</code> per build variant | |
| in the repository, compatible variants first.</p> | |
| `,returnType:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p><code>list[Decision]</code></p> | |
| `}}),Y=new C({props:{title:"get_loaded_kernels",local:"kernels.get_loaded_kernels",headingTag:"h3"}}),A=new Z({props:{name:"kernels.get_loaded_kernels",anchor:"kernels.get_loaded_kernels",parameters:[],source:"https://github.com/huggingface/kernels/blob/vr_607/kernels/src/kernels/utils.py#L142",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p>One <a | |
| href="/docs/kernels/pr_607/en/api/kernels#kernels.LoadedKernel" | |
| >LoadedKernel</a> per distinct kernel variant path | |
| loaded in this process.</p> | |
| `,returnType:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p><code>list[LoadedKernel]</code></p> | |
| `}}),F=new Ut({props:{anchor:"kernels.get_loaded_kernels.example",$$slots:{default:[en]},$$scope:{ctx:pe}}}),O=new C({props:{title:"Loading locked kernels",local:"loading-locked-kernels",headingTag:"h2"}}),ee=new C({props:{title:"load_kernel",local:"kernels.load_kernel",headingTag:"h3"}}),te=new Z({props:{name:"kernels.load_kernel",anchor:"kernels.load_kernel",parameters:[{name:"repo_id",val:": str"},{name:"lockfile",val:": pathlib.Path | None"},{name:"backend",val:": str | None = None"},{name:"revision",val:": str | None = None"}],parametersDescription:[{anchor:"kernels.load_kernel.repo_id",description:`<strong>repo_id</strong> (<code>str</code>) — | |
| The Hub repository containing the kernel.`,name:"repo_id"},{anchor:"kernels.load_kernel.lockfile",description:`<strong>lockfile</strong> (<code>Path</code>, <em>optional</em>) — | |
| Path to the lockfile. If not provided, the lockfile will be loaded from the caller’s package metadata.`,name:"lockfile"},{anchor:"kernels.load_kernel.backend",description:`<strong>backend</strong> (<code>str</code>, <em>optional</em>) — | |
| The backend to load the kernel for. Can only be <code>cpu</code> or the backend that Torch is compiled for. | |
| The backend will be detected automatically if not provided.`,name:"backend"},{anchor:"kernels.load_kernel.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>) — | |
| The specific revision (branch, tag, or commit) to download. Cannot be used together with <code>version</code>.`,name:"revision"}],source:"https://github.com/huggingface/kernels/blob/vr_607/kernels/src/kernels/utils.py#L593",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p>The imported kernel module.</p> | |
| `,returnType:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p><code>ModuleType</code></p> | |
| `}}),ne=new C({props:{title:"get_locked_kernel",local:"kernels.get_locked_kernel",headingTag:"h3"}}),re=new Z({props:{name:"kernels.get_locked_kernel",anchor:"kernels.get_locked_kernel",parameters:[{name:"repo_id",val:": str"},{name:"local_files_only",val:": bool = False"}],parametersDescription:[{anchor:"kernels.get_locked_kernel.repo_id",description:`<strong>repo_id</strong> (<code>str</code>) — | |
| The Hub repository containing the kernel.`,name:"repo_id"},{anchor:"kernels.get_locked_kernel.local_files_only",description:`<strong>local_files_only</strong> (<code>bool</code>, <em>optional</em>, defaults to <code>False</code>) — | |
| Whether to only use local files and not download from the Hub.`,name:"local_files_only"}],source:"https://github.com/huggingface/kernels/blob/vr_607/kernels/src/kernels/utils.py#L649",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p>The imported kernel module.</p> | |
| `,returnType:`<script context="module">export const metadata = 'undefined';<\/script> | |
| <p><code>ModuleType</code></p> | |
| `}}),oe=new C({props:{title:"Classes",local:"classes",headingTag:"h2"}}),le=new C({props:{title:"LoadedKernel",local:"kernels.LoadedKernel",headingTag:"h3"}}),se=new Z({props:{name:"class kernels.LoadedKernel",anchor:"kernels.LoadedKernel",parameters:[{name:"metadata",val:": Metadata"},{name:"module",val:": module"},{name:"repo_info",val:": kernels.utils.RepoInfo | None"}],source:"https://github.com/huggingface/kernels/blob/vr_607/kernels/src/kernels/utils.py#L112"}}),ae=new C({props:{title:"RepoInfo",local:"kernels.RepoInfo",headingTag:"h3"}}),ie=new Z({props:{name:"class kernels.RepoInfo",anchor:"kernels.RepoInfo",parameters:[{name:"repo_id",val:": str"},{name:"revision",val:": str"}],source:"https://github.com/huggingface/kernels/blob/vr_607/kernels/src/kernels/utils.py#L97"}}),de=new At({props:{source:"https://github.com/huggingface/kernels/blob/main/docs/source/api/kernels.md"}}),{c(){u=i("meta"),j=r(),v=i("p"),h=r(),c(_.$$.fragment),a=r(),c(b.$$.fragment),Ee=r(),c(G.$$.fragment),Pe=r(),c(U.$$.fragment),De=r(),y=i("div"),c(B.$$.fragment),lt=r(),me=i("p"),me.textContent=wt,st=r(),ke=i("p"),ke.textContent=Ct,at=r(),c(V.$$.fragment),Re=r(),c(X.$$.fragment),Ze=r(),P=i("div"),c(K.$$.fragment),it=r(),ge=i("p"),ge.textContent=Mt,Ve=r(),c(q.$$.fragment),Fe=r(),D=i("div"),c(S.$$.fragment),dt=r(),fe=i("p"),fe.textContent=Lt,He=r(),c(z.$$.fragment),We=r(),M=i("div"),c(Q.$$.fragment),ct=r(),ue=i("p"),ue.textContent=Nt,pt=r(),he=i("p"),he.textContent=It,Ge=r(),c(Y.$$.fragment),Ue=r(),T=i("div"),c(A.$$.fragment),mt=r(),$e=i("p"),$e.textContent=Jt,kt=r(),_e=i("p"),_e.textContent=jt,gt=r(),c(F.$$.fragment),Be=r(),c(O.$$.fragment),Xe=r(),c(ee.$$.fragment),Ke=r(),L=i("div"),c(te.$$.fragment),ft=r(),ve=i("p"),ve.textContent=Et,ut=r(),be=i("p"),be.innerHTML=Pt,qe=r(),c(ne.$$.fragment),Se=r(),R=i("div"),c(re.$$.fragment),ht=r(),xe=i("p"),xe.textContent=Dt,ze=r(),c(oe.$$.fragment),Qe=r(),c(le.$$.fragment),Ye=r(),x=i("div"),c(se.$$.fragment),$t=r(),ye=i("p"),ye.textContent=Rt,_t=r(),Te=i("ul"),Te.innerHTML=Zt,vt=r(),we=i("p"),we.textContent=Vt,bt=r(),Ce=i("ul"),Ce.innerHTML=Ft,Ae=r(),c(ae.$$.fragment),Oe=r(),w=i("div"),c(ie.$$.fragment),xt=r(),Me=i("p"),Me.textContent=Ht,yt=r(),Le=i("p"),Le.textContent=Wt,Tt=r(),Ne=i("ul"),Ne.innerHTML=Gt,et=r(),c(de.$$.fragment),tt=r(),je=i("p"),this.h()},l(e){const t=Qt("svelte-u9bgzb",document.head);u=d(t,"META",{name:!0,content:!0}),t.forEach(n),j=o(e),v=d(e,"P",{}),I(v).forEach(n),h=o(e),p(_.$$.fragment,e),a=o(e),p(b.$$.fragment,e),Ee=o(e),p(G.$$.fragment,e),Pe=o(e),p(U.$$.fragment,e),De=o(e),y=d(e,"DIV",{class:!0});var N=I(y);p(B.$$.fragment,N),lt=o(N),me=d(N,"P",{"data-svelte-h":!0}),$(me)!=="svelte-v6pak5"&&(me.textContent=wt),st=o(N),ke=d(N,"P",{"data-svelte-h":!0}),$(ke)!=="svelte-1adbar6"&&(ke.textContent=Ct),at=o(N),p(V.$$.fragment,N),N.forEach(n),Re=o(e),p(X.$$.fragment,e),Ze=o(e),P=d(e,"DIV",{class:!0});var ce=I(P);p(K.$$.fragment,ce),it=o(ce),ge=d(ce,"P",{"data-svelte-h":!0}),$(ge)!=="svelte-ysgxyb"&&(ge.textContent=Mt),ce.forEach(n),Ve=o(e),p(q.$$.fragment,e),Fe=o(e),D=d(e,"DIV",{class:!0});var rt=I(D);p(S.$$.fragment,rt),dt=o(rt),fe=d(rt,"P",{"data-svelte-h":!0}),$(fe)!=="svelte-oel36i"&&(fe.textContent=Lt),rt.forEach(n),He=o(e),p(z.$$.fragment,e),We=o(e),M=d(e,"DIV",{class:!0});var Ie=I(M);p(Q.$$.fragment,Ie),ct=o(Ie),ue=d(Ie,"P",{"data-svelte-h":!0}),$(ue)!=="svelte-1l0cwqe"&&(ue.textContent=Nt),pt=o(Ie),he=d(Ie,"P",{"data-svelte-h":!0}),$(he)!=="svelte-98ethb"&&(he.textContent=It),Ie.forEach(n),Ge=o(e),p(Y.$$.fragment,e),Ue=o(e),T=d(e,"DIV",{class:!0});var H=I(T);p(A.$$.fragment,H),mt=o(H),$e=d(H,"P",{"data-svelte-h":!0}),$($e)!=="svelte-hargcl"&&($e.textContent=Jt),kt=o(H),_e=d(H,"P",{"data-svelte-h":!0}),$(_e)!=="svelte-bvc5k7"&&(_e.textContent=jt),gt=o(H),p(F.$$.fragment,H),H.forEach(n),Be=o(e),p(O.$$.fragment,e),Xe=o(e),p(ee.$$.fragment,e),Ke=o(e),L=d(e,"DIV",{class:!0});var Je=I(L);p(te.$$.fragment,Je),ft=o(Je),ve=d(Je,"P",{"data-svelte-h":!0}),$(ve)!=="svelte-1s7s7e5"&&(ve.textContent=Et),ut=o(Je),be=d(Je,"P",{"data-svelte-h":!0}),$(be)!=="svelte-16266qf"&&(be.innerHTML=Pt),Je.forEach(n),qe=o(e),p(ne.$$.fragment,e),Se=o(e),R=d(e,"DIV",{class:!0});var ot=I(R);p(re.$$.fragment,ot),ht=o(ot),xe=d(ot,"P",{"data-svelte-h":!0}),$(xe)!=="svelte-ui0v8u"&&(xe.textContent=Dt),ot.forEach(n),ze=o(e),p(oe.$$.fragment,e),Qe=o(e),p(le.$$.fragment,e),Ye=o(e),x=d(e,"DIV",{class:!0});var E=I(x);p(se.$$.fragment,E),$t=o(E),ye=d(E,"P",{"data-svelte-h":!0}),$(ye)!=="svelte-10yajky"&&(ye.textContent=Rt),_t=o(E),Te=d(E,"UL",{"data-svelte-h":!0}),$(Te)!=="svelte-1133git"&&(Te.innerHTML=Zt),vt=o(E),we=d(E,"P",{"data-svelte-h":!0}),$(we)!=="svelte-eh9buy"&&(we.textContent=Vt),bt=o(E),Ce=d(E,"UL",{"data-svelte-h":!0}),$(Ce)!=="svelte-qcje4a"&&(Ce.innerHTML=Ft),E.forEach(n),Ae=o(e),p(ae.$$.fragment,e),Oe=o(e),w=d(e,"DIV",{class:!0});var W=I(w);p(ie.$$.fragment,W),xt=o(W),Me=d(W,"P",{"data-svelte-h":!0}),$(Me)!=="svelte-1qmhf0s"&&(Me.textContent=Ht),yt=o(W),Le=d(W,"P",{"data-svelte-h":!0}),$(Le)!=="svelte-1j3sm3i"&&(Le.textContent=Wt),Tt=o(W),Ne=d(W,"UL",{"data-svelte-h":!0}),$(Ne)!=="svelte-nl2d40"&&(Ne.innerHTML=Gt),W.forEach(n),et=o(e),p(de.$$.fragment,e),tt=o(e),je=d(e,"P",{}),I(je).forEach(n),this.h()},h(){J(u,"name","hf:doc:metadata"),J(u,"content",nn),J(y,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),J(P,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),J(D,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),J(M,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),J(T,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),J(L,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),J(R,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),J(x,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),J(w,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8")},m(e,t){s(document.head,u),l(e,j,t),l(e,v,t),l(e,h,t),m(_,e,t),l(e,a,t),m(b,e,t),l(e,Ee,t),m(G,e,t),l(e,Pe,t),m(U,e,t),l(e,De,t),l(e,y,t),m(B,y,null),s(y,lt),s(y,me),s(y,st),s(y,ke),s(y,at),m(V,y,null),l(e,Re,t),m(X,e,t),l(e,Ze,t),l(e,P,t),m(K,P,null),s(P,it),s(P,ge),l(e,Ve,t),m(q,e,t),l(e,Fe,t),l(e,D,t),m(S,D,null),s(D,dt),s(D,fe),l(e,He,t),m(z,e,t),l(e,We,t),l(e,M,t),m(Q,M,null),s(M,ct),s(M,ue),s(M,pt),s(M,he),l(e,Ge,t),m(Y,e,t),l(e,Ue,t),l(e,T,t),m(A,T,null),s(T,mt),s(T,$e),s(T,kt),s(T,_e),s(T,gt),m(F,T,null),l(e,Be,t),m(O,e,t),l(e,Xe,t),m(ee,e,t),l(e,Ke,t),l(e,L,t),m(te,L,null),s(L,ft),s(L,ve),s(L,ut),s(L,be),l(e,qe,t),m(ne,e,t),l(e,Se,t),l(e,R,t),m(re,R,null),s(R,ht),s(R,xe),l(e,ze,t),m(oe,e,t),l(e,Qe,t),m(le,e,t),l(e,Ye,t),l(e,x,t),m(se,x,null),s(x,$t),s(x,ye),s(x,_t),s(x,Te),s(x,vt),s(x,we),s(x,bt),s(x,Ce),l(e,Ae,t),m(ae,e,t),l(e,Oe,t),l(e,w,t),m(ie,w,null),s(w,xt),s(w,Me),s(w,yt),s(w,Le),s(w,Tt),s(w,Ne),l(e,et,t),m(de,e,t),l(e,tt,t),l(e,je,t),nt=!0},p(e,[t]){const N={};t&2&&(N.$$scope={dirty:t,ctx:e}),V.$set(N);const ce={};t&2&&(ce.$$scope={dirty:t,ctx:e}),F.$set(ce)},i(e){nt||(k(_.$$.fragment,e),k(b.$$.fragment,e),k(G.$$.fragment,e),k(U.$$.fragment,e),k(B.$$.fragment,e),k(V.$$.fragment,e),k(X.$$.fragment,e),k(K.$$.fragment,e),k(q.$$.fragment,e),k(S.$$.fragment,e),k(z.$$.fragment,e),k(Q.$$.fragment,e),k(Y.$$.fragment,e),k(A.$$.fragment,e),k(F.$$.fragment,e),k(O.$$.fragment,e),k(ee.$$.fragment,e),k(te.$$.fragment,e),k(ne.$$.fragment,e),k(re.$$.fragment,e),k(oe.$$.fragment,e),k(le.$$.fragment,e),k(se.$$.fragment,e),k(ae.$$.fragment,e),k(ie.$$.fragment,e),k(de.$$.fragment,e),nt=!0)},o(e){g(_.$$.fragment,e),g(b.$$.fragment,e),g(G.$$.fragment,e),g(U.$$.fragment,e),g(B.$$.fragment,e),g(V.$$.fragment,e),g(X.$$.fragment,e),g(K.$$.fragment,e),g(q.$$.fragment,e),g(S.$$.fragment,e),g(z.$$.fragment,e),g(Q.$$.fragment,e),g(Y.$$.fragment,e),g(A.$$.fragment,e),g(F.$$.fragment,e),g(O.$$.fragment,e),g(ee.$$.fragment,e),g(te.$$.fragment,e),g(ne.$$.fragment,e),g(re.$$.fragment,e),g(oe.$$.fragment,e),g(le.$$.fragment,e),g(se.$$.fragment,e),g(ae.$$.fragment,e),g(ie.$$.fragment,e),g(de.$$.fragment,e),nt=!1},d(e){e&&(n(j),n(v),n(h),n(a),n(Ee),n(Pe),n(De),n(y),n(Re),n(Ze),n(P),n(Ve),n(Fe),n(D),n(He),n(We),n(M),n(Ge),n(Ue),n(T),n(Be),n(Xe),n(Ke),n(L),n(qe),n(Se),n(R),n(ze),n(Qe),n(Ye),n(x),n(Ae),n(Oe),n(w),n(et),n(tt),n(je)),n(u),f(_,e),f(b,e),f(G,e),f(U,e),f(B),f(V),f(X,e),f(K),f(q,e),f(S),f(z,e),f(Q),f(Y,e),f(A),f(F),f(O,e),f(ee,e),f(te),f(ne,e),f(re),f(oe,e),f(le,e),f(se),f(ae,e),f(ie),f(de,e)}}}const nn='{"title":"Kernels API Reference","local":"kernels-api-reference","sections":[{"title":"Main Functions","local":"main-functions","sections":[{"title":"get_kernel","local":"kernels.get_kernel","sections":[],"depth":3},{"title":"get_local_kernel","local":"kernels.get_local_kernel","sections":[],"depth":3},{"title":"has_kernel","local":"kernels.has_kernel","sections":[],"depth":3},{"title":"get_kernel_variants","local":"kernels.get_kernel_variants","sections":[],"depth":3},{"title":"get_loaded_kernels","local":"kernels.get_loaded_kernels","sections":[],"depth":3}],"depth":2},{"title":"Loading locked kernels","local":"loading-locked-kernels","sections":[{"title":"load_kernel","local":"kernels.load_kernel","sections":[],"depth":3},{"title":"get_locked_kernel","local":"kernels.get_locked_kernel","sections":[],"depth":3}],"depth":2},{"title":"Classes","local":"classes","sections":[{"title":"LoadedKernel","local":"kernels.LoadedKernel","sections":[],"depth":3},{"title":"RepoInfo","local":"kernels.RepoInfo","sections":[],"depth":3}],"depth":2}],"depth":1}';function rn(pe){return qt(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class pn extends St{constructor(u){super(),zt(this,u,rn,tn,Kt,{})}}export{pn as component}; | |
Xet Storage Details
- Size:
- 27 kB
- Xet hash:
- fb0acc5ef026d647b3b6310d9e18ef3daa52267fb7378221d86ac2bb076ab884
·
Xet efficiently stores files, intelligently splitting them into unique chunks and accelerating uploads and downloads. More info.