kernels/pr_512/en/_app/immutable/nodes/2.ae2e4dc7.js

import{s as zt,o as Yt,n as St}from"../chunks/scheduler.f3b1e791.js";import{S as At,i as Ot,e as i,s as l,c,h as en,a as d,d as n,b as r,f as I,g as p,j as h,k as J,l as s,m as o,n as m,t as k,o as u,p as f}from"../chunks/index.023a9934.js";import{C as tn}from"../chunks/CopyLLMTxtMenu.cc24d0e5.js";import{D as H,E as Kt}from"../chunks/ExampleCodeBlock.e146325a.js";import{C as Qt}from"../chunks/CodeBlock.53c436d3.js";import{H as C,E as nn}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.64b97ed6.js";function ln(ke){let g,j="Example:",b,$,_;return $=new Qt({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(){g=i("p"),g.textContent=j,b=l(),c($.$$.fragment)},l(a){g=d(a,"P",{"data-svelte-h":!0}),h(g)!=="svelte-11lpom8"&&(g.textContent=j),b=r(a),p($.$$.fragment,a)},m(a,v){o(a,g,v),o(a,b,v),m($,a,v),_=!0},p:St,i(a){_||(k($.$$.fragment,a),_=!0)},o(a){u($.$$.fragment,a),_=!1},d(a){a&&(n(g),n(b)),f($,a)}}}function rn(ke){let g,j="Example:",b,$,_;return $=new Qt({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">&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.metadata.name, loaded.repo_info)`,wrap:!1}}),{c(){g=i("p"),g.textContent=j,b=l(),c($.$$.fragment)},l(a){g=d(a,"P",{"data-svelte-h":!0}),h(g)!=="svelte-11lpom8"&&(g.textContent=j),b=r(a),p($.$$.fragment,a)},m(a,v){o(a,g,v),o(a,b,v),m($,a,v),_=!0},p:St,i(a){_||(k($.$$.fragment,a),_=!0)},o(a){u($.$$.fragment,a),_=!1},d(a){a&&(n(g),n(b)),f($,a)}}}function on(ke){let g,j,b,$,_,a,v,Ne,W,Pe,G,qe,y,U,it,ue,Mt="Load a kernel from the kernel hub.",dt,fe,Lt=`This function downloads a kernel to the local Hugging Face Hub cache directory (if it was not downloaded before)
and then loads the kernel.`,ct,Z,De,B,He,N,X,pt,ge,It="Import a kernel from a local kernel repository path.",Ze,K,Fe,P,S,mt,he,Jt="Check whether a kernel build exists for the current environment (Torch version and compute framework).",Re,Q,Ve,T,z,kt,$e,jt="Return a snapshot of every kernel that has been loaded into the current process.",ut,_e,Et="The returned list is a new list; mutating it does not affect the registry.",ft,F,We,Y,Ge,A,Ue,M,O,gt,be,Nt="Get a pre-downloaded, locked kernel.",ht,ve,Pt="If <code>lockfile</code> is not specified, the lockfile will be loaded from the caller’s package metadata.",Be,ee,Xe,te,qt="<<<<<<< kernels-use-kernels-data",Ke,q,ne,$t,xe,Dt="Get a kernel using a lock file.",Se,le,Qe,re,ze,x,oe,_t,ye,Ht="This dataclass provides information about a loaded kernel:",bt,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,Ft="The metadata includes the following properties that describe a kernel:",xt,Ce,Rt="<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>",Ye,se,Ae,w,ae,yt,Me,Vt="This dataclass stores the origin of the kernel.",Tt,Le,Wt="The following fields are available:",wt,Ie,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>",Oe,ie,Ut="=======",et,D,de,Ct,Je,Bt="Get a kernel using a lock file.",tt,ce,Xt="<blockquote><blockquote><blockquote><blockquote><blockquote><blockquote><p>main</p></blockquote></blockquote></blockquote></blockquote></blockquote></blockquote>",nt,pe,lt,Ee,rt;return _=new tn({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),v=new C({props:{title:"Kernels API Reference",local:"kernels-api-reference",headingTag:"h1"}}),W=new C({props:{title:"Main Functions",local:"main-functions",headingTag:"h2"}}),G=new C({props:{title:"get_kernel",local:"kernels.get_kernel",headingTag:"h3"}}),U=new H({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>) &#x2014;
The Hub repository containing the kernel.`,name:"repo_id"},{anchor:"kernels.get_kernel.revision",description:`<strong>revision</strong> (<em>str</em>, <em>optional</em>, defaults to <em>&#x201C;main&#x201D;</em>) &#x2014;
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>) &#x2014;
The kernel version to download. Cannot be used together with <em>revision</em>.`,name:"version"},{anchor:"kernels.get_kernel.backend",description:`<strong>backend</strong> (<em>str</em>, <em>optional</em>) &#x2014;
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>) &#x2014;
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>) &#x2014;
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_512/kernels/src/kernels/utils.py#L329",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>
`}}),Z=new Kt({props:{anchor:"kernels.get_kernel.example",$$slots:{default:[ln]},$$scope:{ctx:ke}}}),B=new C({props:{title:"get_local_kernel",local:"kernels.get_local_kernel",headingTag:"h3"}}),X=new H({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>) &#x2014;
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>) &#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_512/kernels/src/kernels/utils.py#L396",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 C({props:{title:"has_kernel",local:"kernels.has_kernel",headingTag:"h3"}}),S=new H({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_512/kernels/src/kernels/utils.py#L429",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>
`}}),Q=new C({props:{title:"get_loaded_kernels",local:"kernels.get_loaded_kernels",headingTag:"h3"}}),z=new H({props:{name:"kernels.get_loaded_kernels",anchor:"kernels.get_loaded_kernels",parameters:[],source:"https://github.com/huggingface/kernels/blob/vr_512/kernels/src/kernels/utils.py#L120",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>One <a
  href="/docs/kernels/pr_512/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 Kt({props:{anchor:"kernels.get_loaded_kernels.example",$$slots:{default:[rn]},$$scope:{ctx:ke}}}),Y=new C({props:{title:"Loading locked kernels",local:"loading-locked-kernels",headingTag:"h2"}}),A=new C({props:{title:"load_kernel",local:"kernels.load_kernel",headingTag:"h3"}}),O=new H({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_512/kernels/src/kernels/utils.py#L469",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>
`}}),ee=new C({props:{title:"get_locked_kernel",local:"kernels.get_locked_kernel",headingTag:"h3"}}),ne=new H({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_512/kernels/src/kernels/utils.py#L539",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>
`}}),le=new C({props:{title:"Classes",local:"classes",headingTag:"h2"}}),re=new C({props:{title:"LoadedKernel",local:"kernels.LoadedKernel",headingTag:"h3"}}),oe=new H({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_512/kernels/src/kernels/utils.py#L90"}}),se=new C({props:{title:"RepoInfo",local:"kernels.RepoInfo",headingTag:"h3"}}),ae=new H({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_512/kernels/src/kernels/utils.py#L75"}}),de=new H({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_512/kernels/src/kernels/utils.py#L539",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>
`}}),pe=new nn({props:{source:"https://github.com/huggingface/kernels/blob/main/docs/source/api/kernels.md"}}),{c(){g=i("meta"),j=l(),b=i("p"),$=l(),c(_.$$.fragment),a=l(),c(v.$$.fragment),Ne=l(),c(W.$$.fragment),Pe=l(),c(G.$$.fragment),qe=l(),y=i("div"),c(U.$$.fragment),it=l(),ue=i("p"),ue.textContent=Mt,dt=l(),fe=i("p"),fe.textContent=Lt,ct=l(),c(Z.$$.fragment),De=l(),c(B.$$.fragment),He=l(),N=i("div"),c(X.$$.fragment),pt=l(),ge=i("p"),ge.textContent=It,Ze=l(),c(K.$$.fragment),Fe=l(),P=i("div"),c(S.$$.fragment),mt=l(),he=i("p"),he.textContent=Jt,Re=l(),c(Q.$$.fragment),Ve=l(),T=i("div"),c(z.$$.fragment),kt=l(),$e=i("p"),$e.textContent=jt,ut=l(),_e=i("p"),_e.textContent=Et,ft=l(),c(F.$$.fragment),We=l(),c(Y.$$.fragment),Ge=l(),c(A.$$.fragment),Ue=l(),M=i("div"),c(O.$$.fragment),gt=l(),be=i("p"),be.textContent=Nt,ht=l(),ve=i("p"),ve.innerHTML=Pt,Be=l(),c(ee.$$.fragment),Xe=l(),te=i("p"),te.textContent=qt,Ke=l(),q=i("div"),c(ne.$$.fragment),$t=l(),xe=i("p"),xe.textContent=Dt,Se=l(),c(le.$$.fragment),Qe=l(),c(re.$$.fragment),ze=l(),x=i("div"),c(oe.$$.fragment),_t=l(),ye=i("p"),ye.textContent=Ht,bt=l(),Te=i("ul"),Te.innerHTML=Zt,vt=l(),we=i("p"),we.textContent=Ft,xt=l(),Ce=i("ul"),Ce.innerHTML=Rt,Ye=l(),c(se.$$.fragment),Ae=l(),w=i("div"),c(ae.$$.fragment),yt=l(),Me=i("p"),Me.textContent=Vt,Tt=l(),Le=i("p"),Le.textContent=Wt,wt=l(),Ie=i("ul"),Ie.innerHTML=Gt,Oe=l(),ie=i("p"),ie.textContent=Ut,et=l(),D=i("div"),c(de.$$.fragment),Ct=l(),Je=i("p"),Je.textContent=Bt,tt=l(),ce=i("blockquote"),ce.innerHTML=Xt,nt=l(),c(pe.$$.fragment),lt=l(),Ee=i("p"),this.h()},l(e){const 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