trackio/pr_310/en/_app/immutable/nodes/11.a8f8bddc.js

import{s as Re,a as Le,n as Ae,o as ze}from"../chunks/scheduler.cfabe6e6.js";import{S as Se,i as Ee,e as i,s as n,c as r,h as Fe,a as p,d as l,b as a,f as Ne,g as o,j as c,k as gt,q as Xe,l as Ve,m as s,n as u,t as m,o as y,p as M}from"../chunks/index.2eae04e0.js";import{C as De,H as T,a as f,E as Pe}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.270b8ab9.js";function Ke(ce){let J,Tt,Mt,ft,U,Jt,h,Ut,w,ht,d,ge=`Trackio helps you organize your experiments within a <strong>project</strong>.
A project is a collection of <strong>runs</strong>, where each run represents a single execution of your code with a specific set of parameters and results.`,wt,j,dt,$,Te='To start tracking an experiment with Trackio, you first need to initialize a project with the <a href="/docs/trackio/pr_310/en/api#trackio.init">init()</a> function:',jt,C,$t,b,fe="<li>If the project already exists, it will be loaded.</li> <li>If not, Trackio will create a new one.</li>",Ct,I,Je="In both cases, a new run is started automatically, ready for you to log data.",bt,k,It,v,Ue=`It’s a good idea to give each run a meaningful name for easier organization and later reference.
You can set a name using the <code>name</code> parameter:`,kt,q,vt,_,he="If no name is provided, Trackio generates a default one.",qt,Q,_t,W,we="You can organize related runs into groups using the <code>group</code> parameter. This is particularly useful when you’re running multiple experiments with different configurations but want to compare them together:",Qt,B,Wt,Z,de='Runs with the same group name can be grouped together in sidebar, making it easier to compare related experiments. You can also group runs by any other configuration parameter (see <a href="#tracking-configuration">Tracking Configuration</a> below).',Bt,Y,Zt,H,je='Once your run is initialized, you can start logging data using the <a href="/docs/trackio/pr_310/en/api#trackio.log">log()</a> function:',Yt,x,Ht,G,$e=`Each call to <a href="/docs/trackio/pr_310/en/api#trackio.log">log()</a> automatically increments the step counter.
If you want to log multiple metrics at once, pass them together:`,xt,N,Gt,R,Nt,L,Ce='You can log tabular data using the <a href="/docs/trackio/pr_310/en/api#trackio.Table">Table</a> class. This is useful for tracking results like predictions, or any structured data.',Rt,A,Lt,g,be="",Ie,At,z,zt,S,ke='You can log images using the <a href="/docs/trackio/pr_310/en/api#trackio.TrackioImage">Image</a> class.',St,E,Et,F,ve="Images can be logged from a path, a numpy array, or a PIL Image.",Ft,X,Xt,V,qe='You can log videos using the <a href="/docs/trackio/pr_310/en/api#trackio.TrackioVideo">Video</a> class.',Vt,D,Dt,P,_e="Videos can be logged from a file path or a numpy array.",Pt,K,Qe="<strong>Numpy array requirements:</strong>",Kt,O,We=`<li>Must be of type <code>np.uint8</code> with RGB values in the range <code>[0, 255]</code></li> <li>Shape should be either:
<ul><li><code>(frames, channels, height, width)</code> for a single video</li> <li><code>(batch, frames, channels, height, width)</code> for multiple videos (will be tiled into a grid)</li></ul></li>`,Ot,tt,te,et,Be=`When your run is complete, finalize it with <a href="/docs/trackio/pr_310/en/api#trackio.finish">finish()</a>.
This marks the run as completed and saves all logged data:`,ee,lt,le,st,se,nt,Ze='If you need to continue a run (for example, after an interruption), you can resume it by calling <a href="/docs/trackio/pr_310/en/api#trackio.init">init()</a> again with the same project and run name, and setting <code>resume=&quot;must&quot;</code>:',ne,at,ae,it,Ye="This will load the existing run so you can keep logging data.",ie,pt,He="For more flexibility, use <code>resume=&quot;allow&quot;</code>. This will resume the run if it exists, or create a new one otherwise.",pe,rt,re,ot,xe='You can also track configuration parameters for your runs. This is useful for keeping track of hyperparameters or other settings used in your experiments. You can log configuration data using the <code>config</code> parameter in the <a href="/docs/trackio/pr_310/en/api#trackio.init">init()</a> function:',oe,ut,ue,mt,Ge="In the dashboard, you can then group by “learning_rate” or “batch_size” to more easily compare runs with different hyperparameters.",me,yt,ye,ct,Me;return U=new De({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),h=new T({props:{title:"Track",local:"track",headingTag:"h1"}}),w=new T({props:{title:"Introduction",local:"introduction",headingTag:"h2"}}),j=new T({props:{title:"Initialization",local:"initialization",headingTag:"h2"}}),C=new f({props:{code:"aW1wb3J0JTIwdHJhY2tpbyUwQSUwQXRyYWNraW8uaW5pdChwcm9qZWN0JTNEJTIybXlfcHJvamVjdCUyMik=",highlighted:`<span class="hljs-keyword">import</span> trackio

trackio.init(project=<span class="hljs-string">&quot;my_project&quot;</span>)`,wrap:!1}}),k=new T({props:{title:"Naming your run",local:"naming-your-run",headingTag:"h3"}}),q=new f({props:{code:"dHJhY2tpby5pbml0KHByb2plY3QlM0QlMjJteV9wcm9qZWN0JTIyJTJDJTIwbmFtZSUzRCUyMm15X2ZpcnN0X3J1biUyMik=",highlighted:'trackio.init(project=<span class="hljs-string">&quot;my_project&quot;</span>, name=<span class="hljs-string">&quot;my_first_run&quot;</span>)',wrap:!1}}),Q=new T({props:{title:"Grouping runs",local:"grouping-runs",headingTag:"h3"}}),B=new f({props:{code:"JTIzJTIwR3JvdXAlMjBydW5zJTIwYnklMjBleHBlcmltZW50JTIwdHlwZSUwQXRyYWNraW8uaW5pdChwcm9qZWN0JTNEJTIybXlfcHJvamVjdCUyMiUyQyUyMG5hbWUlM0QlMjJiYXNlbGluZV9ydW5fMSUyMiUyQyUyMGdyb3VwJTNEJTIyYmFzZWxpbmUlMjIpJTBBdHJhY2tpby5pbml0KHByb2plY3QlM0QlMjJteV9wcm9qZWN0JTIyJTJDJTIwbmFtZSUzRCUyMmF1Z21lbnRlZF9ydW5fMSUyMiUyQyUyMGdyb3VwJTNEJTIyYXVnbWVudGVkJTIyKSUwQXRyYWNraW8uaW5pdChwcm9qZWN0JTNEJTIybXlfcHJvamVjdCUyMiUyQyUyMG5hbWUlM0QlMjJ0dW5lZF9ydW5fMSUyMiUyQyUyMGdyb3VwJTNEJTIydHVuZWQlMjIp",highlighted:`<span class="hljs-comment"># Group runs by experiment type</span>
trackio.init(project=<span class="hljs-string">&quot;my_project&quot;</span>, name=<span class="hljs-string">&quot;baseline_run_1&quot;</span>, group=<span class="hljs-string">&quot;baseline&quot;</span>)
trackio.init(project=<span class="hljs-string">&quot;my_project&quot;</span>, name=<span class="hljs-string">&quot;augmented_run_1&quot;</span>, group=<span class="hljs-string">&quot;augmented&quot;</span>)
trackio.init(project=<span class="hljs-string">&quot;my_project&quot;</span>, name=<span class="hljs-string">&quot;tuned_run_1&quot;</span>, group=<span class="hljs-string">&quot;tuned&quot;</span>)`,wrap:!1}}),Y=new T({props:{title:"Logging Data",local:"logging-data",headingTag:"h2"}}),x=new f({props:{code:"dHJhY2tpby5sb2coJTdCJTIybG9zcyUyMiUzQSUyMDAuMDUlN0Qp",highlighted:'trackio.log({<span class="hljs-string">&quot;loss&quot;</span>: <span class="hljs-number">0.05</span>})',wrap:!1}}),N=new f({props:{code:"dHJhY2tpby5sb2coJTdCJTBBJTIwJTIwJTIwJTIwJTIybG9zcyUyMiUzQSUyMDAuMDUlMkMlMEElMjAlMjAlMjAlMjAlMjJhY2N1cmFjeSUyMiUzQSUyMDAuOTUlMkMlMEElN0Qp",highlighted:`trackio.log({
    <span class="hljs-string">&quot;loss&quot;</span>: <span class="hljs-number">0.05</span>,
    <span class="hljs-string">&quot;accuracy&quot;</span>: <span class="hljs-number">0.95</span>,
})`,wrap:!1}}),R=new T({props:{title:"Logging tables",local:"logging-tables",headingTag:"h3"}}),A=new f({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> pandas <span class="hljs-keyword">as</span> pd

df = pd.DataFrame(
    {
        <span class="hljs-string">&quot;prompt&quot;</span>: [<span class="hljs-string">&quot;Trackio&quot;</span>, <span class="hljs-string">&quot;Logging is&quot;</span>],
        <span class="hljs-string">&quot;completion&quot;</span>: [<span class="hljs-string">&quot;is great!&quot;</span>, <span class="hljs-string">&quot;easy and fun!&quot;</span>],
        <span class="hljs-string">&quot;reward&quot;</span>: [<span class="hljs-number">0.123</span>, <span class="hljs-number">0.456</span>],
    }
)
trackio.log(
    {
        ...
        <span class="hljs-string">&quot;texts&quot;</span>: trackio.Table(dataframe=df),
    }
)`,wrap:!1}}),z=new T({props:{title:"Logging images",local:"logging-images",headingTag:"h3"}}),E=new f({props:{code:"dHJhY2tpby5sb2coJTdCJTIyaW1hZ2UlMjIlM0ElMjB0cmFja2lvLkltYWdlKHZhbHVlJTNEJTIycGF0aCUyRnRvJTJGaW1hZ2UucG5nJTIyJTJDJTIwY2FwdGlvbiUzRCUyMkltYWdlJTIwY2FwdGlvbiUyMiklN0Qp",highlighted:'trackio.log({<span class="hljs-string">&quot;image&quot;</span>: trackio.Image(value=<span class="hljs-string">&quot;path/to/image.png&quot;</span>, caption=<span class="hljs-string">&quot;Image caption&quot;</span>)})',wrap:!1}}),X=new T({props:{title:"Logging videos",local:"logging-videos",headingTag:"h3"}}),D=new f({props:{code:"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",highlighted:`<span class="hljs-keyword">import</span> trackio
<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np

<span class="hljs-comment"># Create a simple video from numpy array</span>
frames = np.random.randint(<span class="hljs-number">0</span>, <span class="hljs-number">255</span>, (<span class="hljs-number">10</span>, <span class="hljs-number">3</span>, <span class="hljs-number">64</span>, <span class="hljs-number">64</span>), dtype=np.uint8)
video = trackio.Video(frames, caption=<span class="hljs-string">&quot;Random video&quot;</span>, fps=<span class="hljs-number">30</span>)
trackio.log({<span class="hljs-string">&quot;my_video&quot;</span>: video})

<span class="hljs-comment"># Create a batch of videos</span>
batch_frames = np.random.randint(<span class="hljs-number">0</span>, <span class="hljs-number">255</span>, (<span class="hljs-number">3</span>, <span class="hljs-number">10</span>, <span class="hljs-number">3</span>, <span class="hljs-number">64</span>, <span class="hljs-number">64</span>), dtype=np.uint8)
batch_video = trackio.Video(batch_frames, caption=<span class="hljs-string">&quot;Batch of videos&quot;</span>, fps=<span class="hljs-number">15</span>)
trackio.log({<span class="hljs-string">&quot;batch_videos&quot;</span>: batch_video})

<span class="hljs-comment"># Create video from file path</span>
video = trackio.Video(<span class="hljs-string">&quot;path/to/video.mp4&quot;</span>, caption=<span class="hljs-string">&quot;Video from file&quot;</span>)
trackio.log({<span class="hljs-string">&quot;file_video&quot;</span>: video})`,wrap:!1}}),tt=new T({props:{title:"Finishing a Run",local:"finishing-a-run",headingTag:"h2"}}),lt=new f({props:{code:"dHJhY2tpby5maW5pc2goKQ==",highlighted:"trackio.finish()",wrap:!1}}),st=new T({props:{title:"Resuming a Run",local:"resuming-a-run",headingTag:"h2"}}),at=new f({props:{code:"dHJhY2tpby5pbml0KHByb2plY3QlM0QlMjJteV9wcm9qZWN0JTIyJTJDJTIwbmFtZSUzRCUyMm15X2ZpcnN0X3J1biUyMiUyQyUyMHJlc3VtZSUzRCUyMm11c3QlMjIp",highlighted:'trackio.init(project=<span class="hljs-string">&quot;my_project&quot;</span>, name=<span class="hljs-string">&quot;my_first_run&quot;</span>, resume=<span class="hljs-string">&quot;must&quot;</span>)',wrap:!1}}),rt=new T({props:{title:"Tracking Configuration",local:"tracking-configuration",headingTag:"h2"}}),ut=new f({props:{code:"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",highlighted:`<span class="hljs-keyword">for</span> batch_size <span class="hljs-keyword">in</span> [<span class="hljs-number">16</span>, <span class="hljs-number">32</span>, <span class="hljs-number">64</span>]:
    <span class="hljs-keyword">for</span> lr <span class="hljs-keyword">in</span> [<span class="hljs-number">0.001</span>, <span class="hljs-number">0.01</span>, <span class="hljs-number">0.1</span>]:
        trackio.init(
            project=<span class="hljs-string">&quot;hyperparameter_tuning&quot;</span>,
            name=<span class="hljs-string">f&quot;lr_<span class="hljs-subst">{lr}</span>_batch_<span class="hljs-subst">{batch_size}</span>_run&quot;</span>,
            config={
                <span class="hljs-string">&quot;learning_rate&quot;</span>: lr,
                <span class="hljs-string">&quot;batch_size&quot;</span>: batch_size,
            }
        )
        <span class="hljs-comment"># ... your training code ...</span>
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