deploy: c4d3bcc

ml-flow/index.html

@@ -780,7 +780,7 @@ <h3 id="starting-mlflow">Starting MLflow<a class="headerlink" href="#starting-ml
 <h3 id="model-saving">Model saving<a class="headerlink" href="#model-saving" title="Permanent link">&para;</a></h3>
 <p>Numalogic provides <code>MLflowRegistry</code>, to save and load models to/from MLflow.</p>
 <p>Here, <code>tracking_uri</code> is the uri where mlflow server is running. The <code>static_keys</code> and <code>dynamic_keys</code> are used to form a unique key for the model.</p>
-<p>The <code>artifact</code> would be the model or transformer object that needs to be saved.
+<p>The <code>artifact</code> would be the model or transformer object that needs to be saved. Artifact saving also takes in 'artifact_type' which is the type of the artifact being saved. Currently, 'pytorch', 'sklearn' and 'pyfunc' is supported.
 A dictionary of metadata can also be saved along with the artifact.
 <div class="highlight"><pre><span></span><code><span class="kn">from</span> <span class="nn">numalogic.registry</span> <span class="kn">import</span> <span class="n">MLflowRegistry</span>
 <span class="kn">from</span> <span class="nn">numalogic.models.autoencoder.variants</span> <span class="kn">import</span> <span class="n">VanillaAE</span>
@@ -793,11 +793,11 @@ <h3 id="model-saving">Model saving<a class="headerlink" href="#model-saving" tit
 
 <span class="n">registry</span> <span class="o">=</span> <span class="n">MLflowRegistry</span><span class="p">(</span><span class="n">tracking_uri</span><span class="o">=</span><span class="s2">&quot;http://0.0.0.0:5000&quot;</span><span class="p">)</span>
 <span class="n">registry</span><span class="o">.</span><span class="n">save</span><span class="p">(</span>
-    <span class="n">skeys</span><span class="o">=</span><span class="n">static_keys</span><span class="p">,</span> <span class="n">dkeys</span><span class="o">=</span><span class="n">dynamic_keys</span><span class="p">,</span> <span class="n">artifact</span><span class="o">=</span><span class="n">model</span><span class="p">,</span> <span class="n">seq_len</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.001</span>
+    <span class="n">skeys</span><span class="o">=</span><span class="n">static_keys</span><span class="p">,</span> <span class="n">dkeys</span><span class="o">=</span><span class="n">dynamic_keys</span><span class="p">,</span> <span class="n">artifact_type</span><span class="o">=</span><span class="s1">&#39;pytorch&#39;</span><span class="p">,</span> <span class="n">artifact</span><span class="o">=</span><span class="n">model</span><span class="p">,</span> <span class="n">seq_len</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.001</span>
 <span class="p">)</span>
 </code></pre></div></p>
 <h3 id="model-loading">Model loading<a class="headerlink" href="#model-loading" title="Permanent link">&para;</a></h3>
-<p>Once, the models are save to MLflow, the <code>load</code> function of <code>MLflowRegistry</code> can be used to load the model.</p>
+<p>Once, the models are save to MLflow, the <code>load</code> function of <code>MLflowRegistry</code> can be used to load the model. Like how the artifacts were saved with 'artifact_type', the same type shall be passed to the <code>load</code> function as well.</p>
 <div class="highlight"><pre><span></span><code><span class="kn">from</span> <span class="nn">numalogic.registry</span> <span class="kn">import</span> <span class="n">MLflowRegistry</span>
 
 <span class="n">static_keys</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;model&quot;</span><span class="p">,</span> <span class="s2">&quot;autoencoder&quot;</span><span class="p">]</span>

sitemap.xml

@@ -2,52 +2,52 @@
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
     <url>
          <loc>None</loc>
-         <lastmod>2024-09-04</lastmod>
+         <lastmod>2024-09-05</lastmod>
          <changefreq>daily</changefreq>
     </url>
 </urlset>