kernels/pr_631/en/_app/immutable/nodes/2.5018bf1e.js

import{s as At,o as Qt,n as jt}from"../chunks/scheduler.f3b1e791.js";import{S as St,i as Yt,e as d,s as r,c as p,h as Kt,a as c,d as n,b as o,f as N,g as m,j as b,k as E,l as a,m as s,n as k,t as u,o as f,p as g}from"../chunks/index.023a9934.js";import{C as Ot}from"../chunks/CopyLLMTxtMenu.37fd950c.js";import{D as V,E as Ct}from"../chunks/ExampleCodeBlock.1b29ae21.js";import{C as Jt}from"../chunks/CodeBlock.d572bf65.js";import{H as j,E as en}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.c5ad2475.js";function tn(F){let i,y="Example:",_,h,$;return h=new Jt({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(){i=d("p"),i.textContent=y,_=r(),p(h.$$.fragment)},l(l){i=c(l,"P",{"data-svelte-h":!0}),b(i)!=="svelte-11lpom8"&&(i.textContent=y),_=o(l),m(h.$$.fragment,l)},m(l,v){s(l,i,v),s(l,_,v),k(h,l,v),$=!0},p:jt,i(l){$||(u(h.$$.fragment,l),$=!0)},o(l){f(h.$$.fragment,l),$=!1},d(l){l&&(n(i),n(_)),g(h,l)}}}function nn(F){let i,y="Example:",_,h,$;return h=new Jt({props:{code:"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",highlighted:` <span class="hljs-keyword">from</span> kernels <span class="hljs-keyword">import</span> get_kernel_variants, VariantAccepted

<span class="hljs-keyword">for</span> decision <span class="hljs-keyword">in</span> get_kernel_variants(<span class="hljs-string">&quot;kernels-community/activation&quot;</span>, version=<span class="hljs-number">1</span>):
    name = decision.variant.variant_str
    <span class="hljs-keyword">if</span> <span class="hljs-built_in">isinstance</span>(decision, VariantAccepted):
        <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;<span class="hljs-subst">{name}</span>: compatible&quot;</span>)
    <span class="hljs-keyword">else</span>:
        <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;<span class="hljs-subst">{name}</span>: rejected (<span class="hljs-subst">{decision.reason}</span>)&quot;</span>)
`,lang:"python",wrap:!1}}),{c(){i=d("p"),i.textContent=y,_=r(),p(h.$$.fragment)},l(l){i=c(l,"P",{"data-svelte-h":!0}),b(i)!=="svelte-11lpom8"&&(i.textContent=y),_=o(l),m(h.$$.fragment,l)},m(l,v){s(l,i,v),s(l,_,v),k(h,l,v),$=!0},p:jt,i(l){$||(u(h.$$.fragment,l),$=!0)},o(l){f(h.$$.fragment,l),$=!1},d(l){l&&(n(i),n(_)),g(h,l)}}}function rn(F){let i,y="Example:",_,h,$;return h=new Jt({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(){i=d("p"),i.textContent=y,_=r(),p(h.$$.fragment)},l(l){i=c(l,"P",{"data-svelte-h":!0}),b(i)!=="svelte-11lpom8"&&(i.textContent=y),_=o(l),m(h.$$.fragment,l)},m(l,v){s(l,i,v),s(l,_,v),k(h,l,v),$=!0},p:jt,i(l){$||(u(h.$$.fragment,l),$=!0)},o(l){f(h.$$.fragment,l),$=!1},d(l){l&&(n(i),n(_)),g(h,l)}}}function on(F){let i,y,_,h,$,l,v,Be,X,Le,q,Ve,T,z,st,fe,It="Load a kernel from the kernel hub.",at,ge,Nt=`This function downloads a kernel to the local Hugging Face Hub cache directory (if it was not downloaded before)
and then loads the kernel.`,it,R,Fe,A,Re,Z,Q,dt,he,Et="Import a kernel from a local kernel repository path.",We,S,Pe,B,Y,ct,$e,Ut="Check whether a kernel build exists for the current environment (Torch version and compute framework).",Ge,K,He,w,O,pt,be,Zt="Resolve all build variants of a kernel against the current environment.",mt,_e,Bt=`The decisions are sorted with compatible variants first, the most preferred
variant leading.`,kt,W,De,ee,Xe,M,te,ut,ve,Lt="Return a snapshot of every kernel that has been loaded into the current process.",ft,xe,Vt="The returned list is a new list; mutating it does not affect the registry.",gt,P,qe,ne,ze,re,Ae,J,oe,ht,ye,Ft="Get a pre-downloaded, locked kernel.",$t,Te,Rt="If <code>lockfile</code> is not specified, the lockfile will be loaded from the caller’s package metadata.",Qe,le,Se,L,se,bt,we,Wt="Get a kernel using a lock file.",Ye,ae,Ke,ie,Oe,x,de,_t,Me,Pt="This dataclass provides information about a loaded kernel:",vt,Ce,Gt=`<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 for kernels loaded
from a known Hub repository, i.e. via <code>get_kernel</code>, <code>get_locked_kernel</code>, or
<code>load_kernel</code>. Only <code>get_local_kernel</code>, which loads from an arbitrary local
path, leaves this as <code>None</code>.</li>`,xt,je,Ht="The metadata includes the following properties that describe a kernel:",yt,Je,Dt="<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 original upstream repository of the kernel.</li> <li><code>source</code> (<code>str | None</code>): the kernel-builder formatted source repository.</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>",et,ce,tt,C,pe,Tt,Ie,Xt="This dataclass stores the origin of the kernel.",wt,Ne,qt="The following fields are available:",Mt,Ee,zt=`<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> <li><code>local</code> (<code>bool</code>): whether the kernel was loaded from pre-downloaded local
files (<code>True</code>) rather than downloaded from the Hub (<code>False</code>).</li>`,nt,me,rt,Ze,ot;return $=new Ot({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),v=new j({props:{title:"Kernels API Reference",local:"kernels-api-reference",headingTag:"h1"}}),X=new j({props:{title:"Main Functions",local:"main-functions",headingTag:"h2"}}),q=new j({props:{title:"get_kernel",local:"kernels.get_kernel",headingTag:"h3"}}),z=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_631/kernels/src/kernels/utils.py#L461",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 Ct({props:{anchor:"kernels.get_kernel.example",$$slots:{default:[tn]},$$scope:{ctx:F}}}),A=new j({props:{title:"get_local_kernel",local:"kernels.get_local_kernel",headingTag:"h3"}}),Q=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_631/kernels/src/kernels/utils.py#L530",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>
`}}),S=new j({props:{title:"has_kernel",local:"kernels.has_kernel",headingTag:"h3"}}),Y=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_631/kernels/src/kernels/utils.py#L566",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>
`}}),K=new j({props:{title:"get_kernel_variants",local:"kernels.get_kernel_variants",headingTag:"h3"}}),O=new V({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>) &#x2014;
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>) &#x2014;
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>) &#x2014;
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>) &#x2014;
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_631/kernels/src/kernels/utils.py#L607",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>
`}}),W=new Ct({props:{anchor:"kernels.get_kernel_variants.example",$$slots:{default:[nn]},$$scope:{ctx:F}}}),ee=new j({props:{title:"get_loaded_kernels",local:"kernels.get_loaded_kernels",headingTag:"h3"}}),te=new V({props:{name:"kernels.get_loaded_kernels",anchor:"kernels.get_loaded_kernels",parameters:[],source:"https://github.com/huggingface/kernels/blob/vr_631/kernels/src/kernels/utils.py#L152",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>One <a
  href="/docs/kernels/pr_631/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>
`}}),P=new Ct({props:{anchor:"kernels.get_loaded_kernels.example",$$slots:{default:[rn]},$$scope:{ctx:F}}}),ne=new j({props:{title:"Loading locked kernels",local:"loading-locked-kernels",headingTag:"h2"}}),re=new j({props:{title:"load_kernel",local:"kernels.load_kernel",headingTag:"h3"}}),oe=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"},{name:"revision",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"},{anchor:"kernels.load_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"}],source:"https://github.com/huggingface/kernels/blob/vr_631/kernels/src/kernels/utils.py#L656",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 j({props:{title:"get_locked_kernel",local:"kernels.get_locked_kernel",headingTag:"h3"}}),se=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_631/kernels/src/kernels/utils.py#L719",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>
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