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Author: Mike

4.1/search/search_index.json

@@ -12,7 +12,7 @@
     <span class=n>inference_helper_columns</span><span class=o>=</span><span class=p>[</span><span class=s2>&quot;expiry_date&quot;</span><span class=p>],</span>
 <span class=p>)</span>
 </code></pre></div> </div> </div> </div> </div> <h3 id=retrieval>Retrieval<a class=headerlink href=#retrieval title="Permanent link">#</a></h3> <p>When retrieving data for model inference, helper columns will be omitted. However, they can be optionally fetched with inference or training data.</p> <h4 id=batch-inference>Batch inference<a class=headerlink href=#batch-inference title="Permanent link">#</a></h4> <div class="tabbed-set tabbed-alternate" data-tabs=2:1><input checked=checked id=__tabbed_2_1 name=__tabbed_2 type=radio><div class=tabbed-labels><label for=__tabbed_2_1>Python</label></div> <div class=tabbed-content> <div class=tabbed-block> <div class="admonition example"> <p class=admonition-title>Fetch inference helper column values and compute on-demand features during batch inference.</p> <div class=highlight><pre><span></span><code><span class=c1># import feature functions</span>
-<span class=kn>from</span> <span class=nn>feature_functions</span> <span class=kn>import</span> <span class=n>time_delta</span>
+<span class=kn>from</span><span class=w> </span><span class=nn>feature_functions</span><span class=w> </span><span class=kn>import</span> <span class=n>time_delta</span>
 
 <span class=c1># Fetch feature view object  </span>
 <span class=n>feature_view</span> <span class=o>=</span> <span class=n>fs</span><span class=o>.</span><span class=n>get_feature_view</span><span class=p>(</span>
@@ -28,7 +28,7 @@
 
 <span class=c1># prepare datatame for prediction</span>
 <span class=n>df</span> <span class=o>=</span> <span class=n>df</span><span class=p>[[</span><span class=n>f</span><span class=o>.</span><span class=n>name</span> <span class=k>for</span> <span class=n>f</span> <span class=ow>in</span> <span class=n>feature_view</span><span class=o>.</span><span class=n>features</span> <span class=k>if</span> <span class=ow>not</span> <span class=p>(</span><span class=n>f</span><span class=o>.</span><span class=n>label</span> <span class=ow>or</span> <span class=n>f</span><span class=o>.</span><span class=n>inference_helper_column</span> <span class=ow>or</span> <span class=n>f</span><span class=o>.</span><span class=n>training_helper_column</span><span class=p>)]]</span>
-</code></pre></div> </div> </div> </div> </div> <h4 id=online-inference>Online inference<a class=headerlink href=#online-inference title="Permanent link">#</a></h4> <div class="tabbed-set tabbed-alternate" data-tabs=3:1><input checked=checked id=__tabbed_3_1 name=__tabbed_3 type=radio><div class=tabbed-labels><label for=__tabbed_3_1>Python</label></div> <div class=tabbed-content> <div class=tabbed-block> <div class="admonition example"> <p class=admonition-title>Fetch inference helper column values and compute on-demand features during online inference.</p> <div class=highlight><pre><span></span><code><span class=kn>from</span> <span class=nn>feature_functions</span> <span class=kn>import</span> <span class=n>time_delta</span>
+</code></pre></div> </div> </div> </div> </div> <h4 id=online-inference>Online inference<a class=headerlink href=#online-inference title="Permanent link">#</a></h4> <div class="tabbed-set tabbed-alternate" data-tabs=3:1><input checked=checked id=__tabbed_3_1 name=__tabbed_3 type=radio><div class=tabbed-labels><label for=__tabbed_3_1>Python</label></div> <div class=tabbed-content> <div class=tabbed-block> <div class="admonition example"> <p class=admonition-title>Fetch inference helper column values and compute on-demand features during online inference.</p> <div class=highlight><pre><span></span><code><span class=kn>from</span><span class=w> </span><span class=nn>feature_functions</span><span class=w> </span><span class=kn>import</span> <span class=n>time_delta</span>
 
 <span class=c1># Fetch feature view object  </span>
 <span class=n>feature_view</span> <span class=o>=</span> <span class=n>fs</span><span class=o>.</span><span class=n>get_feature_view</span><span class=p>(</span>
@@ -70,7 +70,7 @@
     <span class=n>training_helper_columns</span><span class=o>=</span><span class=p>[</span><span class=s2>&quot;category&quot;</span><span class=p>]</span>
 <span class=p>)</span>
 </code></pre></div> </div> </div> </div> </div> <h3 id=retrieval_1>Retrieval<a class=headerlink href=#retrieval_1 title="Permanent link">#</a></h3> <p>When retrieving training data helper columns will be omitted. However, they can be optionally fetched.</p> <div class="tabbed-set tabbed-alternate" data-tabs=5:1><input checked=checked id=__tabbed_5_1 name=__tabbed_5 type=radio><div class=tabbed-labels><label for=__tabbed_5_1>Python</label></div> <div class=tabbed-content> <div class=tabbed-block> <div class="admonition example"> <p class=admonition-title>Fetch training data with or without inference helper column values.</p> <div class=highlight><pre><span></span><code><span class=c1># import feature functions</span>
-<span class=kn>from</span> <span class=nn>feature_functions</span> <span class=kn>import</span> <span class=n>location_delta</span><span class=p>,</span> <span class=n>time_delta</span>
+<span class=kn>from</span><span class=w> </span><span class=nn>feature_functions</span><span class=w> </span><span class=kn>import</span> <span class=n>location_delta</span><span class=p>,</span> <span class=n>time_delta</span>
 
 <span class=c1># Fetch feature view object  </span>
 <span class=n>feature_view</span> <span class=o>=</span> <span class=n>fs</span><span class=o>.</span><span class=n>get_feature_view</span><span class=p>(</span>