kernels/pr_490/en/_app/immutable/nodes/2.07c86c2f.js

import{s as dt,o as it,n as at}from"../chunks/scheduler.f3b1e791.js";import{S as ct,i as pt,e as i,s as r,c as p,h as mt,a as c,d as n,b as o,f as L,g as m,j as y,k as P,l as s,m as a,n as k,t as g,o as f,p as u}from"../chunks/index.023a9934.js";import{C as kt}from"../chunks/CopyLLMTxtMenu.3af54d86.js";import{D as me,E as lt}from"../chunks/ExampleCodeBlock.225c1249.js";import{C as st}from"../chunks/CodeBlock.ecff0838.js";import{H as I,E as gt}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.699f7a6c.js";function ft(A){let d,C="Example:",b,h,$;return h=new st({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,b=r(),p(h.$$.fragment)},l(l){d=c(l,"P",{"data-svelte-h":!0}),y(d)!=="svelte-11lpom8"&&(d.textContent=C),b=o(l),m(h.$$.fragment,l)},m(l,v){a(l,d,v),a(l,b,v),k(h,l,v),$=!0},p:at,i(l){$||(g(h.$$.fragment,l),$=!0)},o(l){f(h.$$.fragment,l),$=!1},d(l){l&&(n(d),n(b)),u(h,l)}}}function ut(A){let d,C="Example:",b,h,$;return h=new st({props:{code:"ZnJvbSUyMGtlcm5lbHMlMjBpbXBvcnQlMjBnZXRfa2VybmVsJTJDJTIwZ2V0X2xvYWRlZF9rZXJuZWxzJTBBJTBBZ2V0X2tlcm5lbCglMjJrZXJuZWxzLWNvbW11bml0eSUyRmFjdGl2YXRpb24lMjIlMkMlMjB2ZXJzaW9uJTNEMSklMEFmb3IlMjBsb2FkZWQlMjBpbiUyMGdldF9sb2FkZWRfa2VybmVscygpJTNBJTBBJTIwJTIwJTIwJTIwcHJpbnQobG9hZGVkLnBhY2thZ2VfbmFtZSUyQyUyMGxvYWRlZC5yZXBvX2luZm9zKQ==",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.package_name, loaded.repo_infos)`,wrap:!1}}),{c(){d=i("p"),d.textContent=C,b=r(),p(h.$$.fragment)},l(l){d=c(l,"P",{"data-svelte-h":!0}),y(d)!=="svelte-11lpom8"&&(d.textContent=C),b=o(l),m(h.$$.fragment,l)},m(l,v){a(l,d,v),a(l,b,v),k(h,l,v),$=!0},p:at,i(l){$||(g(h.$$.fragment,l),$=!0)},o(l){f(h.$$.fragment,l),$=!1},d(l){l&&(n(d),n(b)),u(h,l)}}}function ht(A){let d,C,b,h,$,l,v,ge,B,fe,G,ue,T,H,Ze,O,Se="Load a kernel from the kernel hub.",Le,ee,ze=`This function downloads a kernel to the local Hugging Face Hub cache directory (if it was not downloaded before)
and then loads the kernel.`,Pe,E,he,D,_e,J,U,Be,te,Qe="Import a kernel from a local kernel repository path.",$e,V,be,j,F,Ge,ne,Ye="Check whether a kernel build exists for the current environment (Torch version and compute framework).",ve,R,xe,_,W,He,re,Ke="Return a snapshot of every kernel that has been loaded into the current process.",De,oe,Ae="Each entry is a <code>kernels.utils.LoadedKernel</code> namedtuple with fields:",Ue,le,Oe=`<li><code>module</code> (<code>ModuleType</code>): the imported kernel module.</li> <li><code>package_name</code> (<code>str</code>): the kernel’s package 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>`,Ve,ae,et=`<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,se,tt="The returned list is a new list; mutating it does not affect the registry.",Re,Z,ye,X,Te,q,we,w,S,We,de,nt="Get a pre-downloaded, locked kernel.",Xe,ie,rt="If <code>lockfile</code> is not specified, the lockfile will be loaded from the caller’s package metadata.",Me,z,Ce,N,Q,qe,ce,ot="Get a kernel using a lock file.",Je,Y,je,ke,Ne;return $=new kt({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),v=new I({props:{title:"Kernels API Reference",local:"kernels-api-reference",headingTag:"h1"}}),B=new I({props:{title:"Main Functions",local:"main-functions",headingTag:"h2"}}),G=new I({props:{title:"get_kernel",local:"kernels.get_kernel",headingTag:"h3"}}),H=new me({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_490/kernels/src/kernels/utils.py#L289",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 lt({props:{anchor:"kernels.get_kernel.example",$$slots:{default:[ft]},$$scope:{ctx:A}}}),D=new I({props:{title:"get_local_kernel",local:"kernels.get_local_kernel",headingTag:"h3"}}),U=new me({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_490/kernels/src/kernels/utils.py#L348",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>
`}}),V=new I({props:{title:"has_kernel",local:"kernels.has_kernel",headingTag:"h3"}}),F=new me({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_490/kernels/src/kernels/utils.py#L384",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>
`}}),R=new I({props:{title:"get_loaded_kernels",local:"kernels.get_loaded_kernels",headingTag:"h3"}}),W=new me({props:{name:"kernels.get_loaded_kernels",anchor:"kernels.get_loaded_kernels",parameters:[],source:"https://github.com/huggingface/kernels/blob/vr_490/kernels/src/kernels/utils.py#L51",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 lt({props:{anchor:"kernels.get_loaded_kernels.example",$$slots:{default:[ut]},$$scope:{ctx:A}}}),X=new I({props:{title:"Loading locked kernels",local:"loading-locked-kernels",headingTag:"h2"}}),q=new I({props:{title:"load_kernel",local:"kernels.load_kernel",headingTag:"h3"}}),S=new me({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_490/kernels/src/kernels/utils.py#L429",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>
`}}),z=new I({props:{title:"get_locked_kernel",local:"kernels.get_locked_kernel",headingTag:"h3"}}),Q=new me({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_490/kernels/src/kernels/utils.py#L502",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>
`}}),Y=new gt({props:{source:"https://github.com/huggingface/kernels/blob/main/docs/source/api/kernels.md"}}),{c(){d=i("meta"),C=r(),b=i("p"),h=r(),p($.$$.fragment),l=r(),p(v.$$.fragment),ge=r(),p(B.$$.fragment),fe=r(),p(G.$$.fragment),ue=r(),T=i("div"),p(H.$$.fragment),Ze=r(),O=i("p"),O.textContent=Se,Le=r(),ee=i("p"),ee.textContent=ze,Pe=r(),p(E.$$.fragment),he=r(),p(D.$$.fragment),_e=r(),J=i("div"),p(U.$$.fragment),Be=r(),te=i("p"),te.textContent=Qe,$e=r(),p(V.$$.fragment),be=r(),j=i("div"),p(F.$$.fragment),Ge=r(),ne=i("p"),ne.textContent=Ye,ve=r(),p(R.$$.fragment),xe=r(),_=i("div"),p(W.$$.fragment),He=r(),re=i("p"),re.textContent=Ke,De=r(),oe=i("p"),oe.innerHTML=Ae,Ue=r(),le=i("ul"),le.innerHTML=Oe,Ve=r(),ae=i("p"),ae.innerHTML=et,Fe=r(),se=i("p"),se.textContent=tt,Re=r(),p(Z.$$.fragment),ye=r(),p(X.$$.fragment),Te=r(),p(q.$$.fragment),we=r(),w=i("div"),p(S.$$.fragment),We=r(),de=i("p"),de.textContent=nt,Xe=r(),ie=i("p"),ie.innerHTML=rt,Me=r(),p(z.$$.fragment),Ce=r(),N=i("div"),p(Q.$$.fragment),qe=r(),ce=i("p"),ce.textContent=ot,Je=r(),p(Y.$$.fragment),je=r(),ke=i("p"),this.h()},l(e){const 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