kernels/pr_577/en/_app/immutable/nodes/2.3bd1872a.js

import{s as Pt,o as Zt,n as Et}from"../chunks/scheduler.f3b1e791.js";import{S as Rt,i as Ft,e as i,s as r,c,h as Dt,a as d,d as n,b as l,f as j,g as p,j as $,k as E,l as s,m as o,n as m,t as k,o as f,p as g}from"../chunks/index.023a9934.js";import{C as Ht}from"../chunks/CopyLLMTxtMenu.5f3b0c01.js";import{D as V,E as jt}from"../chunks/ExampleCodeBlock.282a89fe.js";import{C as Nt}from"../chunks/CodeBlock.fbf79025.js";import{H as C,E as Vt}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.3cccf7b6.js";function Wt(ie){let u,I="Example:",b,h,_;return h=new Nt({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)`,lang:"python",wrap:!1}}),{c(){u=i("p"),u.textContent=I,b=r(),c(h.$$.fragment)},l(a){u=d(a,"P",{"data-svelte-h":!0}),$(u)!=="svelte-11lpom8"&&(u.textContent=I),b=l(a),p(h.$$.fragment,a)},m(a,v){o(a,u,v),o(a,b,v),m(h,a,v),_=!0},p:Et,i(a){_||(k(h.$$.fragment,a),_=!0)},o(a){f(h.$$.fragment,a),_=!1},d(a){a&&(n(u),n(b)),g(h,a)}}}function Gt(ie){let u,I="Example:",b,h,_;return h=new Nt({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)`,lang:"python",wrap:!1}}),{c(){u=i("p"),u.textContent=I,b=r(),c(h.$$.fragment)},l(a){u=d(a,"P",{"data-svelte-h":!0}),$(u)!=="svelte-11lpom8"&&(u.textContent=I),b=l(a),p(h.$$.fragment,a)},m(a,v){o(a,u,v),o(a,b,v),m(h,a,v),_=!0},p:Et,i(a){_||(k(h.$$.fragment,a),_=!0)},o(a){f(h.$$.fragment,a),_=!1},d(a){a&&(n(u),n(b)),g(h,a)}}}function Ut(ie){let u,I,b,h,_,a,v,Me,W,Le,G,Ie,y,U,Ye,de,gt="Load a kernel from the kernel hub.",Ae,ce,ut=`This function downloads a kernel to the local Hugging Face Hub cache directory (if it was not downloaded before)
and then loads the kernel.`,Oe,R,Je,B,je,N,X,et,pe,ht="Import a kernel from a local kernel repository path.",Ee,K,Ne,P,S,tt,me,$t="Check whether a kernel build exists for the current environment (Torch version and compute framework).",Pe,q,Ze,T,z,nt,ke,_t="Return a snapshot of every kernel that has been loaded into the current process.",rt,fe,bt="The returned list is a new list; mutating it does not affect the registry.",lt,F,Re,Q,Fe,Y,De,M,A,ot,ge,vt="Get a pre-downloaded, locked kernel.",st,ue,xt="If <code>lockfile</code> is not specified, the lockfile will be loaded from the caller’s package metadata.",He,O,Ve,Z,ee,at,he,yt="Get a kernel using a lock file.",We,te,Ge,ne,Ue,x,re,it,$e,Tt="This dataclass provides information about a loaded kernel:",dt,_e,wt=`<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>`,ct,be,Ct="The metadata includes the following properties that describe a kernel:",pt,ve,Mt="<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>",Be,le,Xe,w,oe,mt,xe,Lt="This dataclass stores the origin of the kernel.",kt,ye,It="The following fields are available:",ft,Te,Jt="<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>",Ke,se,Se,Ce,qe;return _=new Ht({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 V({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>) &#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>.
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>) &#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_577/kernels/src/kernels/utils.py#L339",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>
`}}),R=new jt({props:{anchor:"kernels.get_kernel.example",$$slots:{default:[Wt]},$$scope:{ctx:ie}}}),B=new C({props:{title:"get_local_kernel",local:"kernels.get_local_kernel",headingTag:"h3"}}),X=new V({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_577/kernels/src/kernels/utils.py#L407",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 V({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>) &#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>.
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>) &#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_577/kernels/src/kernels/utils.py#L440",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 V({props:{name:"kernels.get_loaded_kernels",anchor:"kernels.get_loaded_kernels",parameters:[],source:"https://github.com/huggingface/kernels/blob/vr_577/kernels/src/kernels/utils.py#L130",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>One <a
  href="/docs/kernels/pr_577/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 jt({props:{anchor:"kernels.get_loaded_kernels.example",$$slots:{default:[Gt]},$$scope:{ctx:ie}}}),Q=new C({props:{title:"Loading locked kernels",local:"loading-locked-kernels",headingTag:"h2"}}),Y=new C({props:{title:"load_kernel",local:"kernels.load_kernel",headingTag:"h3"}}),A=new V({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_577/kernels/src/kernels/utils.py#L481",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>
`}}),O=new C({props:{title:"get_locked_kernel",local:"kernels.get_locked_kernel",headingTag:"h3"}}),ee=new V({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_577/kernels/src/kernels/utils.py#L551",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>
`}}),te=new C({props:{title:"Classes",local:"classes",headingTag:"h2"}}),ne=new C({props:{title:"LoadedKernel",local:"kernels.LoadedKernel",headingTag:"h3"}}),re=new V({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_577/kernels/src/kernels/utils.py#L100"}}),le=new C({props:{title:"RepoInfo",local:"kernels.RepoInfo",headingTag:"h3"}}),oe=new V({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_577/kernels/src/kernels/utils.py#L85"}}),se=new 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