kernels/pr_497/en/_app/immutable/nodes/2.45c5ced3.js

import{s as pt,o as mt,n as it}from"../chunks/scheduler.f3b1e791.js";import{S as kt,i as ut,e as i,s as o,c as m,h as gt,a as c,d as n,b as r,f as P,g as k,j as T,k as L,l as s,m as a,n as u,t as g,o as f,p as h}from"../chunks/index.023a9934.js";import{C as ft}from"../chunks/CopyLLMTxtMenu.ad54ccfb.js";import{D as ke,E as dt}from"../chunks/ExampleCodeBlock.b3399119.js";import{C as ct}from"../chunks/CodeBlock.fe29511e.js";import{H as N,E as ht}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.5a9046c0.js";function _t(O){let d,C="Example:",v,_,$;return _=new ct({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">&quot;kernels-community/relu&quot;</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">&quot;cuda&quot;</span>)
out = torch.empty_like(x)
result = activation.relu(out, x)`,wrap:!1}}),{c(){d=i("p"),d.textContent=C,v=o(),m(_.$$.fragment)},l(l){d=c(l,"P",{"data-svelte-h":!0}),T(d)!=="svelte-11lpom8"&&(d.textContent=C),v=r(l),k(_.$$.fragment,l)},m(l,x){a(l,d,x),a(l,v,x),u(_,l,x),$=!0},p:it,i(l){$||(g(_.$$.fragment,l),$=!0)},o(l){f(_.$$.fragment,l),$=!1},d(l){l&&(n(d),n(v)),h(_,l)}}}function $t(O){let d,C="Example:",v,_,$;return _=new ct({props:{code:"ZnJvbSUyMGtlcm5lbHMlMjBpbXBvcnQlMjBnZXRfa2VybmVsJTJDJTIwZ2V0X2xvYWRlZF9rZXJuZWxzJTBBJTBBZ2V0X2tlcm5lbCglMjJrZXJuZWxzLWNvbW11bml0eSUyRmFjdGl2YXRpb24lMjIlMkMlMjB2ZXJzaW9uJTNEMSklMEFmb3IlMjBsb2FkZWQlMjBpbiUyMGdldF9sb2FkZWRfa2VybmVscygpJTNBJTBBJTIwJTIwJTIwJTIwcHJpbnQobG9hZGVkLm1vZHVsZV9uYW1lJTJDJTIwbG9hZGVkLnJlcG9faW5mb3Mp",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">&quot;kernels-community/activation&quot;</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.module_name, loaded.repo_infos)`,wrap:!1}}),{c(){d=i("p"),d.textContent=C,v=o(),m(_.$$.fragment)},l(l){d=c(l,"P",{"data-svelte-h":!0}),T(d)!=="svelte-11lpom8"&&(d.textContent=C),v=r(l),k(_.$$.fragment,l)},m(l,x){a(l,d,x),a(l,v,x),u(_,l,x),$=!0},p:it,i(l){$||(g(_.$$.fragment,l),$=!0)},o(l){f(_.$$.fragment,l),$=!1},d(l){l&&(n(d),n(v)),h(_,l)}}}function bt(O){let d,C,v,_,$,l,x,ge,H,fe,G,he,y,V,Ze,ee,Qe="Load a kernel from the kernel hub.",Pe,te,Ye=`This function downloads a kernel to the local Hugging Face Hub cache directory (if it was not downloaded before)
and then loads the kernel.`,He,E,_e,D,$e,J,B,Ge,ne,Ke="Import a kernel from a local kernel repository path.",be,U,ve,j,W,Ve,oe,Ae="Check whether a kernel build exists for the current environment (Torch version and compute framework).",xe,F,Te,p,R,De,re,Oe="Return a snapshot of every kernel that has been loaded into the current process.",Be,le,et="Each entry is a <code>kernels.utils.LoadedKernel</code> dataclass with fields:",Ue,ae,tt=`<li><code>kernel_id</code> (<code>str</code>): unique identifier used as the <code>sys.modules</code> key
for this variant (either <code>metadata.id</code> or a hash-suffixed module name).</li> <li><code>module</code> (<code>ModuleType</code>): the imported kernel module.</li> <li><code>module_name</code> (<code>str</code>): the kernel’s module name.</li> <li><code>repo_infos</code> (<code>kernels.utils.RepoInfos | 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>`,We,se,nt=`<code>RepoInfos</code> has <code>repo_id</code>, <code>revision</code>, and <code>backend</code> fields. <code>backend</code>
reflects the value passed by the caller — it is <code>None</code> when the caller
relied on backend auto-detection.`,Fe,de,ot="The returned list is a new list; mutating it does not affect the registry.",Re,q,rt="<p>These arguments might be renamed / changed a bit.</p>",qe,Z,ye,X,we,S,Me,w,z,Xe,ie,lt="Get a pre-downloaded, locked kernel.",Se,ce,at="If <code>lockfile</code> is not specified, the lockfile will be loaded from the caller’s package metadata.",Ce,Q,Je,I,Y,ze,pe,st="Get a kernel using a lock file.",je,K,Ie,ue,Le;return $=new ft({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),x=new N({props:{title:"Kernels API Reference",local:"kernels-api-reference",headingTag:"h1"}}),H=new N({props:{title:"Main Functions",local:"main-functions",headingTag:"h2"}}),G=new N({props:{title:"get_kernel",local:"kernels.get_kernel",headingTag:"h3"}}),V=new ke({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"}],parametersDescription:[{anchor:"kernels.get_kernel.repo_id",description:`<strong>repo_id</strong> (<code>str</code>) &#x2014;
The Hub repository containing the kernel.`,name:"repo_id"},{anchor:"kernels.get_kernel.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>, defaults to <code>&quot;main&quot;</code>) &#x2014;
The specific revision (branch, tag, or commit) to download. Cannot be used together with <code>version</code>.`,name:"revision"},{anchor:"kernels.get_kernel.version",description:`<strong>version</strong> (<code>int</code>, <em>optional</em>) &#x2014;
The kernel version to download. Cannot be used together with <code>revision</code>.`,name:"version"},{anchor:"kernels.get_kernel.backend",description:`<strong>backend</strong> (<code>str</code>, <em>optional</em>) &#x2014;
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.get_kernel.user_agent",description:`<strong>user_agent</strong> (<code>Union[str, dict]</code>, <em>optional</em>) &#x2014;
The <code>user_agent</code> info to pass to <code>snapshot_download()</code> for internal telemetry.`,name:"user_agent"}],source:"https://github.com/huggingface/kernels/blob/vr_497/kernels/src/kernels/utils.py#L309",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>
`}}),E=new dt({props:{anchor:"kernels.get_kernel.example",$$slots:{default:[_t]},$$scope:{ctx:O}}}),D=new N({props:{title:"get_local_kernel",local:"kernels.get_local_kernel",headingTag:"h3"}}),B=new ke({props:{name:"kernels.get_local_kernel",anchor:"kernels.get_local_kernel",parameters:[{name:"repo_path",val:": Path"},{name:"package_name",val:": str"},{name:"backend",val:": str | None = None"}],parametersDescription:[{anchor:"kernels.get_local_kernel.repo_path",description:`<strong>repo_path</strong> (<code>Path</code>) &#x2014;
The local path to the kernel repository.`,name:"repo_path"},{anchor:"kernels.get_local_kernel.package_name",description:`<strong>package_name</strong> (<code>str</code>) &#x2014;
The name of the package to import from the repository.`,name:"package_name"},{anchor:"kernels.get_local_kernel.backend",description:`<strong>backend</strong> (<code>str</code>, <em>optional</em>) &#x2014;
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_497/kernels/src/kernels/utils.py#L368",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>
`}}),U=new N({props:{title:"has_kernel",local:"kernels.has_kernel",headingTag:"h3"}}),W=new ke({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>) &#x2014;
The Hub repository containing the kernel.`,name:"repo_id"},{anchor:"kernels.has_kernel.revision",description:`<strong>revision</strong> (<code>str</code>, <em>optional</em>, defaults to <code>&quot;main&quot;</code>) &#x2014;
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>) &#x2014;
The kernel version to download. Cannot be used together with <code>revision</code>.`,name:"version"},{anchor:"kernels.has_kernel.backend",description:`<strong>backend</strong> (<code>str</code>, <em>optional</em>) &#x2014;
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_497/kernels/src/kernels/utils.py#L404",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>
`}}),F=new N({props:{title:"get_loaded_kernels",local:"kernels.get_loaded_kernels",headingTag:"h3"}}),R=new ke({props:{name:"kernels.get_loaded_kernels",anchor:"kernels.get_loaded_kernels",parameters:[],source:"https://github.com/huggingface/kernels/blob/vr_497/kernels/src/kernels/utils.py#L54",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>one entry 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>
`}}),Z=new dt({props:{anchor:"kernels.get_loaded_kernels.example",$$slots:{default:[$t]},$$scope:{ctx:O}}}),X=new N({props:{title:"Loading locked kernels",local:"loading-locked-kernels",headingTag:"h2"}}),S=new N({props:{title:"load_kernel",local:"kernels.load_kernel",headingTag:"h3"}}),z=new ke({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"}],parametersDescription:[{anchor:"kernels.load_kernel.repo_id",description:`<strong>repo_id</strong> (<code>str</code>) &#x2014;
The Hub repository containing the kernel.`,name:"repo_id"},{anchor:"kernels.load_kernel.lockfile",description:`<strong>lockfile</strong> (<code>Path</code>, <em>optional</em>) &#x2014;
Path to the lockfile. If not provided, the lockfile will be loaded from the caller&#x2019;s package metadata.`,name:"lockfile"},{anchor:"kernels.load_kernel.backend",description:`<strong>backend</strong> (<code>str</code>, <em>optional</em>) &#x2014;
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_497/kernels/src/kernels/utils.py#L449",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 N({props:{title:"get_locked_kernel",local:"kernels.get_locked_kernel",headingTag:"h3"}}),Y=new ke({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>) &#x2014;
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>) &#x2014;
Whether to only use local files and not download from the Hub.`,name:"local_files_only"}],source:"https://github.com/huggingface/kernels/blob/vr_497/kernels/src/kernels/utils.py#L522",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>
`}}),K=new ht({props:{source:"https://github.com/huggingface/kernels/blob/main/docs/source/api/kernels.md"}}),{c(){d=i("meta"),C=o(),v=i("p"),_=o(),m($.$$.fragment),l=o(),m(x.$$.fragment),ge=o(),m(H.$$.fragment),fe=o(),m(G.$$.fragment),he=o(),y=i("div"),m(V.$$.fragment),Ze=o(),ee=i("p"),ee.textContent=Qe,Pe=o(),te=i("p"),te.textContent=Ye,He=o(),m(E.$$.fragment),_e=o(),m(D.$$.fragment),$e=o(),J=i("div"),m(B.$$.fragment),Ge=o(),ne=i("p"),ne.textContent=Ke,be=o(),m(U.$$.fragment),ve=o(),j=i("div"),m(W.$$.fragment),Ve=o(),oe=i("p"),oe.textContent=Ae,xe=o(),m(F.$$.fragment),Te=o(),p=i("div"),m(R.$$.fragment),De=o(),re=i("p"),re.textContent=Oe,Be=o(),le=i("p"),le.innerHTML=et,Ue=o(),ae=i("ul"),ae.innerHTML=tt,We=o(),se=i("p"),se.innerHTML=nt,Fe=o(),de=i("p"),de.textContent=ot,Re=o(),q=i("blockquote"),q.innerHTML=rt,qe=o(),m(Z.$$.fragment),ye=o(),m(X.$$.fragment),we=o(),m(S.$$.fragment),Me=o(),w=i("div"),m(z.$$.fragment),Xe=o(),ie=i("p"),ie.textContent=lt,Se=o(),ce=i("p"),ce.innerHTML=at,Ce=o(),m(Q.$$.fragment),Je=o(),I=i("div"),m(Y.$$.fragment),ze=o(),pe=i("p"),pe.textContent=st,je=o(),m(K.$$.fragment),Ie=o(),ue=i("p"),this.h()},l(e){const 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