From d28d3ac59ac1ab154888ba846893d22d07290f48 Mon Sep 17 00:00:00 2001
From: Joshua Bell <jsbell@chromium.org>
Date: Fri, 31 Jan 2025 04:21:58 +0000
Subject: [PATCH] Editorial: Various style and wording tweaks (#797)

SHA: 74b5ae530f935d08d9d9359f8caaf761cc16db6c
Reason: push, by fdwr

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
---
 index.html | 482 ++++++++++++++++++++++++++---------------------------
 1 file changed, 241 insertions(+), 241 deletions(-)

diff --git a/index.html b/index.html
index 1f2f1468..466eed93 100644
--- a/index.html
+++ b/index.html
@@ -5,9 +5,9 @@
   <title>Web Neural Network API</title>
   <meta content="ED" name="w3c-status">
   <link href="https://www.w3.org/StyleSheets/TR/2021/W3C-ED" rel="stylesheet">
-  <meta content="Bikeshed version c67c745b1, updated Fri Jan 17 14:27:28 2025 -0800" name="generator">
+  <meta content="Bikeshed version c2797e6ab, updated Thu Jan 30 16:24:26 2025 -0800" name="generator">
   <link href="https://www.w3.org/TR/webnn/" rel="canonical">
-  <meta content="2139976ff81d8ddd2c01555a16db45f279bc18f8" name="revision">
+  <meta content="74b5ae530f935d08d9d9359f8caaf761cc16db6c" name="revision">
   <meta content="dark light" name="color-scheme">
   <link href="https://www.w3.org/StyleSheets/TR/2021/dark.css" media="(prefers-color-scheme: dark)" rel="stylesheet" type="text/css">
 <style>
@@ -1018,7 +1018,7 @@
   <div class="head">
    <p data-fill-with="logo"><a class="logo" href="https://www.w3.org/"> <img alt="W3C" height="48" src="https://www.w3.org/StyleSheets/TR/2021/logos/W3C" width="72"> </a> </p>
    <h1 class="p-name no-ref" id="title">Web Neural Network API</h1>
-   <p id="w3c-state"><a href="https://www.w3.org/standards/types/#ED">Editor’s Draft</a>, <time class="dt-updated" datetime="2025-01-29">29 January 2025</time></p>
+   <p id="w3c-state"><a href="https://www.w3.org/standards/types/#ED">Editor’s Draft</a>, <time class="dt-updated" datetime="2025-01-31">31 January 2025</time></p>
    <details open>
     <summary>More details about this document</summary>
     <div data-fill-with="spec-metadata">
@@ -2851,7 +2851,7 @@ <h4 class="heading settled" data-level="7.9.5" id="api-mlgraphbuilder-argminmax"
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/argMin(input, axis, options), MLGraphBuilder/argMax(input, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-argmin-input-axis-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlargminmaxoptions" id="ref-for-dictdef-mlargminmaxoptions③">MLArgMinMaxOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⑧">MLOperand</a></code>. The N-D tensor of the reduced shape. The values must be of type <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlargminmaxoptions-outputdatatype" id="ref-for-dom-mlargminmaxoptions-outputdatatype①">outputDataType</a></code> in the range [0, N-1] where N is the size of the input dimension specified by axis.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑤⑧">MLOperand</a></code>. The N-D tensor of the reduced shape. The values must be of type <code class="idl"><a data-link-type="idl" href="#dom-mlargminmaxoptions-outputdatatype" id="ref-for-dom-mlargminmaxoptions-outputdatatype①">outputDataType</a></code> in the range [0, N-1] where N is the size of the input dimension specified by <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-argmin-input-axis-options-axis" id="ref-for-dom-mlgraphbuilder-argmin-input-axis-options-axis②">axis</a></code>.</p>
    </div>
    <table class="data" id="constraints-argMin-argMax">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-argmin" id="ref-for-dom-mlgraphbuilder-argmin①">argMin()</a></code>/<code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-argmax" id="ref-for-dom-mlgraphbuilder-argmax①">argMax()</a></code></caption>
@@ -2995,7 +2995,7 @@ <h4 class="heading settled" data-level="7.9.6" id="api-mlgraphbuilder-batchnorm"
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/batchNormalization(input, mean, variance, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlbatchnormalizationoptions" id="ref-for-dictdef-mlbatchnormalizationoptions②">MLBatchNormalizationOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦①">MLOperand</a></code>. The batch-normalized N-D tensor of the same shape as <em>input</em>.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦①">MLOperand</a></code>. The batch-normalized N-D tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input①">input</a></code>.</p>
    </div>
    <table class="data" id="constraints-batchNormalization">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization" id="ref-for-dom-mlgraphbuilder-batchnormalization①">batchNormalization()</a></code></caption>
@@ -3006,29 +3006,29 @@ <h4 class="heading settled" data-level="7.9.6" id="api-mlgraphbuilder-batchnorm"
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks②">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①">N</a>
      <tr>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-mean" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-mean①">mean</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input②">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input③">input</a></code>
       <td>1
      <tr>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-variance" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-variance①">variance</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input④">input</a></code>
       <td>1
      <tr>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mlbatchnormalizationoptions-scale" id="ref-for-dom-mlbatchnormalizationoptions-scale①">scale</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input④">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input⑤">input</a></code>
       <td>1
      <tr>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mlbatchnormalizationoptions-bias" id="ref-for-dom-mlbatchnormalizationoptions-bias①">bias</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as③">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input⑤">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as③">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input⑥">input</a></code>
       <td>1
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input⑥">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input⑦">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input⑦">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input" id="ref-for-dom-mlgraphbuilder-batchnormalization-input-mean-variance-options-input⑧">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlbatchnormalizationsupportlimits" id="ref-for-dictdef-mlbatchnormalizationsupportlimits①">MLBatchNormalizationSupportLimits</a></code> has the following members:</p>
    <dl>
@@ -3156,7 +3156,7 @@ <h4 class="heading settled" data-level="7.9.7" id="api-mlgraphbuilder-cast"><spa
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/cast(input, type, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-cast-input-type-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions④">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦⑤">MLOperand</a></code>. The N-D tensor of the same shape as <em>input</em> with each element casted to the target data type.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦⑤">MLOperand</a></code>. The N-D tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-input①">input</a></code> with each element casted to the target data type.</p>
    </div>
    <table class="data" id="constraints-cast">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast" id="ref-for-dom-mlgraphbuilder-cast①">cast()</a></code></caption>
@@ -3167,13 +3167,13 @@ <h4 class="heading settled" data-level="7.9.7" id="api-mlgraphbuilder-cast"><spa
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks③">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-input②">input</a></code>
       <td><a data-link-type="dfn" href="#any-data-type" id="ref-for-any-data-type①">any</a>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank②">N</a>
      <tr>
       <td><em>output</em>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-type" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-type①">type</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-input②">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-input③">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑧">MLOpSupportLimits</a></code> has the following members for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast" id="ref-for-dom-mlgraphbuilder-cast②">cast()</a></code>:</p>
    <dl>
@@ -3183,7 +3183,7 @@ <h4 class="heading settled" data-level="7.9.7" id="api-mlgraphbuilder-cast"><spa
    </dl>
    <p>Casting between <code class="idl"><a data-link-type="idl" href="#enumdef-mloperanddatatype" id="ref-for-enumdef-mloperanddatatype②⓪">MLOperandDataType</a></code>s is specified for some cases and <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#implementation-defined" id="ref-for-implementation-defined⑧">implementation-defined</a> in other cases, according to the following table:</p>
    <table class="grid">
-    <caption> Behavior of the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast" id="ref-for-dom-mlgraphbuilder-cast④">cast()</a></code> operation given the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-input③">input</a></code>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①⓪">dataType</a> (rows) and target <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-type" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-type②">type</a></code> (columns). </caption>
+    <caption> Behavior of the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast" id="ref-for-dom-mlgraphbuilder-cast④">cast()</a></code> operation given the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-input" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-input④">input</a></code>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①⓪">dataType</a> (rows) and target <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-cast-input-type-options-type" id="ref-for-dom-mlgraphbuilder-cast-input-type-options-type②">type</a></code> (columns). </caption>
     <tbody>
      <tr>
       <th class="split"> <span class="top-right">Target type</span> <span class="bottom-left">Input type</span> 
@@ -3267,7 +3267,7 @@ <h4 class="heading settled" data-level="7.9.8" id="api-mlgraphbuilder-clamp"><sp
      <strong>Returns:</strong> 
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦⑨">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑦⑨">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp-input-options-input" id="ref-for-dom-mlgraphbuilder-clamp-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-clamp">
@@ -3279,13 +3279,13 @@ <h4 class="heading settled" data-level="7.9.8" id="api-mlgraphbuilder-clamp"><sp
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks④">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp-input-options-input" id="ref-for-dom-mlgraphbuilder-clamp-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp-input-options-input" id="ref-for-dom-mlgraphbuilder-clamp-input-options-input②">input</a></code>
       <td><a data-link-type="dfn" href="#any-data-type" id="ref-for-any-data-type②">any</a>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank③">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp-input-options-input" id="ref-for-dom-mlgraphbuilder-clamp-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp-input-options-input" id="ref-for-dom-mlgraphbuilder-clamp-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp-input-options-input" id="ref-for-dom-mlgraphbuilder-clamp-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp-input-options-input" id="ref-for-dom-mlgraphbuilder-clamp-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits①⓪">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp" id="ref-for-dom-mlgraphbuilder-clamp③">clamp()</a></code>:</p>
    <dl>
@@ -3382,7 +3382,7 @@ <h4 class="heading settled" data-level="7.9.9" id="api-mlgraphbuilder-concat"><s
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/concat(inputs, axis, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-concat-inputs-axis-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧③">MLOperand</a></code>. The concatenated tensor of all the inputs along
-    the <em>axis</em>. The output tensor has the same shape except on the dimension
+    the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-concat-inputs-axis-options-axis" id="ref-for-dom-mlgraphbuilder-concat-inputs-axis-options-axis①">axis</a></code>. The output tensor has the same shape except on the dimension
     that all the inputs concatenated along. The size of that dimension is
     computed as the sum of all the input sizes of the same dimension.</p>
    </div>
@@ -3578,14 +3578,14 @@ <h4 class="heading settled" data-level="7.9.10" id="api-mlgraphbuilder-conv2d"><
     <ul>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/conv2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-conv2d-input-filter-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑧⑨">MLOperand</a></code>. The input 4-D tensor. The logical shape
-is interpreted according to the value of <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-inputlayout" id="ref-for-dom-mlconv2doptions-inputlayout①">inputLayout</a></code>.</p>
+is interpreted according to the value of <code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-inputlayout" id="ref-for-dom-mlconv2doptions-inputlayout①">inputLayout</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/conv2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-conv2d-input-filter-options-filter"><code>filter</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⓪">MLOperand</a></code>. The filter 4-D tensor. The logical shape is
-interpreted according to the value of <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-filterlayout" id="ref-for-dom-mlconv2doptions-filterlayout①">filterLayout</a></code> and <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups①">groups</a></code>.</p>
+interpreted according to the value of <code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-filterlayout" id="ref-for-dom-mlconv2doptions-filterlayout①">filterLayout</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups①">groups</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/conv2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-conv2d-input-filter-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mlconv2doptions" id="ref-for-dictdef-mlconv2doptions②">MLConv2dOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨①">MLOperand</a></code>. The output 4-D tensor that contains the convolution result. The output shape is interpreted according to the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-inputlayout" id="ref-for-dom-mlconv2doptions-inputlayout②">inputLayout</a></code> value. More specifically, the spatial dimensions or the sizes of the last two dimensions of the output tensor for the <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw③">"nchw"</a></code> input layout can be calculated as follows:</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨①">MLOperand</a></code>. The output 4-D tensor that contains the convolution result. The output shape is interpreted according to <code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-inputlayout" id="ref-for-dom-mlconv2doptions-inputlayout②">inputLayout</a></code>. More specifically, the spatial dimensions or the sizes of the last two dimensions of the output tensor for the <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw③">"nchw"</a></code> input layout can be calculated as follows:</p>
     <p><code>outputSize = 1 + (inputSize - (filterSize - 1) * dilation - 1 + beginningPadding + endingPadding) / stride</code></p>
    </div>
    <table class="data" id="constraints-conv2d">
@@ -3634,7 +3634,7 @@ <h4 class="heading settled" data-level="7.9.10" id="api-mlgraphbuilder-conv2d"><
     <dd data-md>
      <p>Support limits for operator <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-conv2d" id="ref-for-dom-mlgraphbuilder-conv2d④">conv2d()</a></code>.</p>
    </dl>
-   <div class="note" role="note"> A <em>depthwise</em> conv2d operation is a variant of grouped convolution, used in models like the MobileNet, where the <em>options.groups</em> = inputChannels = outputChannels and the shape of filter tensor is <em>[options.groups, 1, height, width]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-oihw" id="ref-for-dom-mlconv2dfilteroperandlayout-oihw①">"oihw"</a></code> layout, <em>[height, width, 1, options.groups]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-hwio" id="ref-for-dom-mlconv2dfilteroperandlayout-hwio①">"hwio"</a></code> layout, <em>[options.groups, height, width, 1]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-ohwi" id="ref-for-dom-mlconv2dfilteroperandlayout-ohwi①">"ohwi"</a></code> layout and <em>[1, height, width, options.groups]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-ihwo" id="ref-for-dom-mlconv2dfilteroperandlayout-ihwo①">"ihwo"</a></code> layout. </div>
+   <div class="note" role="note"> A <em>depthwise</em> conv2d operation is a variant of grouped convolution, used in models like the MobileNet, where the <code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups②">groups</a></code> = <em>inputChannels</em> = <em>outputChannels</em> and the shape of filter tensor is <em>[options.groups, 1, height, width]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-oihw" id="ref-for-dom-mlconv2dfilteroperandlayout-oihw①">"oihw"</a></code> layout, <em>[height, width, 1, options.groups]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-hwio" id="ref-for-dom-mlconv2dfilteroperandlayout-hwio①">"hwio"</a></code> layout, <em>[options.groups, height, width, 1]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-ohwi" id="ref-for-dom-mlconv2dfilteroperandlayout-ohwi①">"ohwi"</a></code> layout and <em>[1, height, width, options.groups]</em> for <code class="idl"><a data-link-type="idl" href="#dom-mlconv2dfilteroperandlayout-ihwo" id="ref-for-dom-mlconv2dfilteroperandlayout-ihwo①">"ihwo"</a></code> layout. </div>
    <details class="algorithm" data-algorithm="calculate conv output size" data-algorithm-for="MLGraphBuilder" open>
     <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-calculate-conv-output-size">calculate conv output size</dfn> given unsigned integers <var>inputSize</var>, <var>filterSize</var>, <var>beginningPadding</var>, <var>endingPadding</var>, <var>stride</var> and <var>dilation</var>, perform these steps. They return a number. </summary>
     <ol>
@@ -3689,7 +3689,7 @@ <h4 class="heading settled" data-level="7.9.10" id="api-mlgraphbuilder-conv2d"><
      <li data-md>
       <p>If any element in <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-dilations" id="ref-for-dom-mlconv2doptions-dilations③">dilations</a></code> is equal to 0, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑥④">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑥⓪">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups②">groups</a></code> is 0, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑥⑤">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑥①">TypeError</a></code>.</p>
+      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups③">groups</a></code> is 0, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑥⑤">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑥①">TypeError</a></code>.</p>
      <li data-md>
       <p><em>Calculate the output shape:</em></p>
       <ol>
@@ -3724,9 +3724,9 @@ <h4 class="heading settled" data-level="7.9.10" id="api-mlgraphbuilder-conv2d"><
           <p>Let « <var>outputChannels</var>, <var>filterInputChannels</var>, <var>filterHeight</var>, <var>filterWidth</var> » be <var>filterShape</var>.</p>
         </dl>
        <li data-md>
-        <p>If <var>inputChannels</var> % <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups③">groups</a></code> is not 0, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑥⑥">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑥②">TypeError</a></code>.</p>
+        <p>If <var>inputChannels</var> % <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups④">groups</a></code> is not 0, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑥⑥">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑥②">TypeError</a></code>.</p>
        <li data-md>
-        <p>Otherwise, if <var>inputChannels</var> / <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups④">groups</a></code> is not equal to <var>filterInputChannels</var>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑥⑦">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑥③">TypeError</a></code>.</p>
+        <p>Otherwise, if <var>inputChannels</var> / <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-groups" id="ref-for-dom-mlconv2doptions-groups⑤">groups</a></code> is not equal to <var>filterInputChannels</var>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw⑥⑦">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror⑥③">TypeError</a></code>.</p>
        <li data-md>
         <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlconv2doptions-bias" id="ref-for-dom-mlconv2doptions-bias③">bias</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists①④">exists</a>:</p>
         <ol>
@@ -3820,7 +3820,7 @@ <h4 class="heading settled" data-level="7.9.11" id="api-mlgraphbuilder-convtrans
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLConvTranspose2dOptions" data-dfn-type="dict-member" data-export id="dom-mlconvtranspose2doptions-outputpadding"><code>outputPadding</code></dfn>, <span> of type <code class="idl-code">sequence&lt;[EnforceRange] unsigned long></code></span>
     <dd data-md>
      <p>A list of length 2.
-Specifies the padding values applied to each spatial dimension of the output tensor. The explicit padding values are needed to disambiguate the output tensor shape for transposed convolution when the value of the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-strides" id="ref-for-dom-mlconvtranspose2doptions-strides①">strides</a></code> is greater than 1.</p>
+Specifies the padding values applied to each spatial dimension of the output tensor. The explicit padding values are needed to disambiguate the output tensor shape for transposed convolution when the value of the <code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-strides" id="ref-for-dom-mlconvtranspose2doptions-strides①">strides</a></code> is greater than 1.</p>
      <p>Note that these values are only used to disambiguate output shape when needed; it does not necessarily cause any padding value to be written to the output tensor.</p>
      <p>The default value is [0, 0].</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLConvTranspose2dOptions" data-dfn-type="dict-member" data-export id="dom-mlconvtranspose2doptions-outputsizes"><code>outputSizes</code></dfn>, <span> of type <code class="idl-code">sequence&lt;[EnforceRange] unsigned long></code></span>
@@ -3872,14 +3872,14 @@ <h4 class="heading settled" data-level="7.9.11" id="api-mlgraphbuilder-convtrans
     <ul>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/convTranspose2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-convtranspose2d-input-filter-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑦">MLOperand</a></code>. The input 4-D tensor. The logical shape
-is interpreted according to the value of <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-inputlayout" id="ref-for-dom-mlconvtranspose2doptions-inputlayout①">inputLayout</a></code>.</p>
+is interpreted according to the value of <code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-inputlayout" id="ref-for-dom-mlconvtranspose2doptions-inputlayout①">inputLayout</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/convTranspose2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-convtranspose2d-input-filter-options-filter"><code>filter</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑧">MLOperand</a></code>. The filter 4-D tensor. The logical shape is
-interpreted according to the value of <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-filterlayout" id="ref-for-dom-mlconvtranspose2doptions-filterlayout①">filterLayout</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-groups" id="ref-for-dom-mlconvtranspose2doptions-groups①">groups</a></code>.</p>
+interpreted according to the value of <code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-filterlayout" id="ref-for-dom-mlconvtranspose2doptions-filterlayout①">filterLayout</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-groups" id="ref-for-dom-mlconvtranspose2doptions-groups①">groups</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/convTranspose2d(input, filter, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-convtranspose2d-input-filter-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlconvtranspose2doptions" id="ref-for-dictdef-mlconvtranspose2doptions②">MLConvTranspose2dOptions</a></code>.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑨">MLOperand</a></code>. The output 4-D tensor that contains the transposed convolution result. The output shape is interpreted according to the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-inputlayout" id="ref-for-dom-mlconvtranspose2doptions-inputlayout②">inputLayout</a></code> value. More specifically, unless the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-outputsizes" id="ref-for-dom-mlconvtranspose2doptions-outputsizes①">outputSizes</a></code> values are explicitly specified, the <em>options</em>.<code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-outputpadding" id="ref-for-dom-mlconvtranspose2doptions-outputpadding②">outputPadding</a></code> is needed to compute the spatial dimension values of the output tensor as follows:</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand⑨⑨">MLOperand</a></code>. The output 4-D tensor that contains the transposed convolution result. The output shape is interpreted according to <code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-inputlayout" id="ref-for-dom-mlconvtranspose2doptions-inputlayout②">inputLayout</a></code>. More specifically, unless <code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-outputsizes" id="ref-for-dom-mlconvtranspose2doptions-outputsizes①">outputSizes</a></code> is explicitly specified, <code class="idl"><a data-link-type="idl" href="#dom-mlconvtranspose2doptions-outputpadding" id="ref-for-dom-mlconvtranspose2doptions-outputpadding②">outputPadding</a></code> is needed to compute the spatial dimension values of the output tensor as follows:</p>
     <p><code>outputSize = (inputSize - 1) * stride + (filterSize - 1) * dilation + 1 - beginningPadding - endingPadding + outputPadding</code></p>
    </div>
    <table class="data" id="constraints-convTranspose2d">
@@ -4909,7 +4909,7 @@ <h4 class="heading settled" data-level="7.9.15" id="api-mlgraphbuilder-elu"><spa
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⓪">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⓪">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-elu-input-options-input" id="ref-for-dom-mlgraphbuilder-elu-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-elu">
@@ -4921,13 +4921,13 @@ <h4 class="heading settled" data-level="7.9.15" id="api-mlgraphbuilder-elu"><spa
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks①⑤">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-elu-input-options-input" id="ref-for-dom-mlgraphbuilder-elu-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-elu-input-options-input" id="ref-for-dom-mlgraphbuilder-elu-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32①⑨">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①⑦">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①⓪">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as①⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-elu-input-options-input" id="ref-for-dom-mlgraphbuilder-elu-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-elu-input-options-input" id="ref-for-dom-mlgraphbuilder-elu-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as①⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-elu-input-options-input" id="ref-for-dom-mlgraphbuilder-elu-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-elu-input-options-input" id="ref-for-dom-mlgraphbuilder-elu-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits②④">MLOpSupportLimits</a></code> has the following members for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-elu" id="ref-for-dom-mlgraphbuilder-elu②">elu()</a></code>:</p>
    <dl>
@@ -5093,13 +5093,13 @@ <h4 class="heading settled" data-level="7.9.17" id="api-mlgraphbuilder-gather"><
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gather(input, indices, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gather-input-indices-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⑧">MLOperand</a></code>. The input N-D tensor from which the values are gathered.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gather(input, indices, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gather-input-indices-options-indices"><code>indices</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⑨">MLOperand</a></code>. The indices N-D tensor of the input values to gather. The values must be of type <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32④">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint32" id="ref-for-dom-mloperanddatatype-uint32③">"uint32"</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int64" id="ref-for-dom-mloperanddatatype-int64③">"int64"</a></code>, and must be in the range -N (inclusive) to N (exclusive) where N is the size of the input dimension indexed by <em>options.axis</em>, and a negative index means indexing from the end of the dimension.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gather(input, indices, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gather-input-indices-options-indices"><code>indices</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑧⑨">MLOperand</a></code>. The indices N-D tensor of the input values to gather. The values must be of type <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32④">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint32" id="ref-for-dom-mloperanddatatype-uint32③">"uint32"</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int64" id="ref-for-dom-mloperanddatatype-int64③">"int64"</a></code>, and must be in the range -N (inclusive) to N (exclusive) where N is the size of the input dimension indexed by <code class="idl"><a data-link-type="idl" href="#dom-mlgatheroptions-axis" id="ref-for-dom-mlgatheroptions-axis①">axis</a></code>, and a negative index means indexing from the end of the dimension.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gather(input, indices, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gather-input-indices-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlgatheroptions" id="ref-for-dictdef-mlgatheroptions②">MLGatherOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨⓪">MLOperand</a></code>. The output N-D tensor of <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②④">rank</a> equal to the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②⑤">rank</a> of <em>input</em> + the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②⑥">rank</a> of <em>indices</em> - 1.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨⓪">MLOperand</a></code>. The output N-D tensor of <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②④">rank</a> equal to the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②⑤">rank</a> of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-input" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-input①">input</a></code> + the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②⑥">rank</a> of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices①">indices</a></code> - 1.</p>
    </div>
-   <div class="note" role="note"> The <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices①">indices</a></code> parameter to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather" id="ref-for-dom-mlgraphbuilder-gather①">gather()</a></code> can not be clamped to the allowed range when the graph is built because the inputs are not known until execution. Implementations can introduce <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp" id="ref-for-dom-mlgraphbuilder-clamp⑤">clamp()</a></code> in the compiled graph if the specified clamping behavior is not provided by the underlying platform. Similarly, if the underlying platform does not support negative indices, the implementation can introduce operations in the compiled graph to transform a negative index from the end of the dimension into a positive index. </div>
+   <div class="note" role="note"> The <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices②">indices</a></code> parameter to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather" id="ref-for-dom-mlgraphbuilder-gather①">gather()</a></code> can not be clamped to the allowed range when the graph is built because the inputs are not known until execution. Implementations can introduce <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-clamp" id="ref-for-dom-mlgraphbuilder-clamp⑤">clamp()</a></code> in the compiled graph if the specified clamping behavior is not provided by the underlying platform. Similarly, if the underlying platform does not support negative indices, the implementation can introduce operations in the compiled graph to transform a negative index from the end of the dimension into a positive index. </div>
    <table class="data" id="constraints-gather">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather" id="ref-for-dom-mlgraphbuilder-gather②">gather()</a></code></caption>
     <thead>
@@ -5109,17 +5109,17 @@ <h4 class="heading settled" data-level="7.9.17" id="api-mlgraphbuilder-gather"><
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks①⑦">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-input" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-input" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-input②">input</a></code>
       <td><a data-link-type="dfn" href="#any-data-type" id="ref-for-any-data-type⑥">any</a>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①②">N</a>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices②">indices</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices③">indices</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32⑤">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint32" id="ref-for-dom-mloperanddatatype-uint32④">"uint32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int64" id="ref-for-dom-mloperanddatatype-int64④">"int64"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①③">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as②⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-input" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-input②">input</a></code>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-input" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-input③">input</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②⑦">rank</a> + <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices③">indices</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②⑧">rank</a> - 1
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as②⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-input" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-input③">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-input" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-input④">input</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②⑦">rank</a> + <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gather-input-indices-options-indices" id="ref-for-dom-mlgraphbuilder-gather-input-indices-options-indices④">indices</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank②⑧">rank</a> - 1
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlgathersupportlimits" id="ref-for-dictdef-mlgathersupportlimits①">MLGatherSupportLimits</a></code> has the following members:</p>
    <dl>
@@ -5153,7 +5153,7 @@ <h4 class="heading settled" data-level="7.9.17" id="api-mlgraphbuilder-gather"><
      <li data-md>
       <p>Let <var>shapeIndices</var> be <var>indices</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape③⓪">shape</a>.</p>
      <li data-md>
-      <p>Let <var>axis</var> be <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgatheroptions-axis" id="ref-for-dom-mlgatheroptions-axis①">axis</a></code>.</p>
+      <p>Let <var>axis</var> be <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgatheroptions-axis" id="ref-for-dom-mlgatheroptions-axis②">axis</a></code>.</p>
      <li data-md>
       <p>If <var>axis</var> is greater than or equal to <var>rankInput</var>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⑥④">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⓪①">TypeError</a></code>.</p>
      <li data-md>
@@ -5292,7 +5292,7 @@ <h4 class="heading settled" data-level="7.9.18" id="api-mlgraphbuilder-gelu-meth
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨④">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand①⑨④">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gelu-input-options-input" id="ref-for-dom-mlgraphbuilder-gelu-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-gelu">
@@ -5304,13 +5304,13 @@ <h4 class="heading settled" data-level="7.9.18" id="api-mlgraphbuilder-gelu-meth
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks①⑧">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gelu-input-options-input" id="ref-for-dom-mlgraphbuilder-gelu-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gelu-input-options-input" id="ref-for-dom-mlgraphbuilder-gelu-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32②⓪">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16①⑧">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①④">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as②①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gelu-input-options-input" id="ref-for-dom-mlgraphbuilder-gelu-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gelu-input-options-input" id="ref-for-dom-mlgraphbuilder-gelu-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as②①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gelu-input-options-input" id="ref-for-dom-mlgraphbuilder-gelu-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gelu-input-options-input" id="ref-for-dom-mlgraphbuilder-gelu-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits③⓪">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gelu" id="ref-for-dom-mlgraphbuilder-gelu②">gelu()</a></code>:</p>
    <dl>
@@ -5388,13 +5388,13 @@ <h4 class="heading settled" data-level="7.9.19" id="api-mlgraphbuilder-gemm"><sp
    <dl>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGemmOptions" data-dfn-type="dict-member" data-export id="dom-mlgemmoptions-c"><code>c</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand①⑨⑨">MLOperand</a></span>
     <dd data-md>
-     <p>The third input tensor. It is either a scalar, or of the shape that is <a data-link-type="dfn" href="#unidirectionally-broadcastable" id="ref-for-unidirectionally-broadcastable③">unidirectionally broadcastable</a> to the shape <em>[M, N]</em>. When it is not specified, the computation is done as if <em>c</em> is a scalar 0.0.</p>
+     <p>The third input tensor. It is either a scalar, or of the shape that is <a data-link-type="dfn" href="#unidirectionally-broadcastable" id="ref-for-unidirectionally-broadcastable③">unidirectionally broadcastable</a> to the shape <em>[M, N]</em>. When it is not specified, the computation is done as if <code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c①">c</a></code> is a scalar 0.0.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGemmOptions" data-dfn-type="dict-member" data-export id="dom-mlgemmoptions-alpha"><code>alpha</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double⑦">double</a>, defaulting to <code>1.0</code></span>
     <dd data-md>
      <p>A multiplier for the first input.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGemmOptions" data-dfn-type="dict-member" data-export id="dom-mlgemmoptions-beta"><code>beta</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double⑧">double</a>, defaulting to <code>1.0</code></span>
     <dd data-md>
-     <p>A multiplier for the third input <code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c①">c</a></code>.</p>
+     <p>A multiplier for the third input <code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c②">c</a></code>.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGemmOptions" data-dfn-type="dict-member" data-export id="dom-mlgemmoptions-atranspose"><code>aTranspose</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean①③">boolean</a>, defaulting to <code>false</code></span>
     <dd data-md>
      <p>Indicates if the first input is transposed prior to calculating the output.</p>
@@ -5406,9 +5406,9 @@ <h4 class="heading settled" data-level="7.9.19" id="api-mlgraphbuilder-gemm"><sp
      <strong>Arguments:</strong> 
     <ul>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⓪⓪">MLOperand</a></code>. The first input 2-D tensor with shape <em>[M, K]</em> if <em>aTranspose</em> is false, or <em>[K, M]</em> if <em>aTranspose</em> is true.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-a"><code>a</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⓪⓪">MLOperand</a></code>. The first input 2-D tensor with shape <em>[M, K]</em> if <code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-atranspose" id="ref-for-dom-mlgemmoptions-atranspose①">aTranspose</a></code> is false, or <em>[K, M]</em> if <code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-atranspose" id="ref-for-dom-mlgemmoptions-atranspose②">aTranspose</a></code> is true.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⓪①">MLOperand</a></code>. The second input 2-D tensor with shape <em>[K, N]</em> if <em>bTranspose</em> is false, or <em>[N, K]</em> if <em>bTranspose</em> is true.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-b"><code>b</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⓪①">MLOperand</a></code>. The second input 2-D tensor with shape <em>[K, N]</em> if <code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-btranspose" id="ref-for-dom-mlgemmoptions-btranspose①">bTranspose</a></code> is false, or <em>[N, K]</em> if <code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-btranspose" id="ref-for-dom-mlgemmoptions-btranspose②">bTranspose</a></code> is true.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gemm(a, b, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gemm-a-b-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlgemmoptions" id="ref-for-dictdef-mlgemmoptions②">MLGemmOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
@@ -5431,7 +5431,7 @@ <h4 class="heading settled" data-level="7.9.19" id="api-mlgraphbuilder-gemm"><sp
       <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as②②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gemm-a-b-options-a" id="ref-for-dom-mlgraphbuilder-gemm-a-b-options-a②">a</a></code>
       <td>2
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c②">c</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c③">c</a></code>
       <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as②③">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gemm-a-b-options-a" id="ref-for-dom-mlgraphbuilder-gemm-a-b-options-a③">a</a></code>
       <td>0 to 2
      <tr>
@@ -5480,13 +5480,13 @@ <h4 class="heading settled" data-level="7.9.19" id="api-mlgraphbuilder-gemm"><sp
      <li data-md>
       <p>Let <var>shapeB</var> be a <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-clone" id="ref-for-list-clone③">clone</a> of <var>b</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape③②">shape</a>.</p>
      <li data-md>
-      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-atranspose" id="ref-for-dom-mlgemmoptions-atranspose①">aTranspose</a></code> is true, then reverse the order of the items in <var>shapeA</var>.</p>
+      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-atranspose" id="ref-for-dom-mlgemmoptions-atranspose③">aTranspose</a></code> is true, then reverse the order of the items in <var>shapeA</var>.</p>
      <li data-md>
-      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-btranspose" id="ref-for-dom-mlgemmoptions-btranspose①">bTranspose</a></code> is true, then reverse the order of the items in <var>shapeB</var>.</p>
+      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-btranspose" id="ref-for-dom-mlgemmoptions-btranspose③">bTranspose</a></code> is true, then reverse the order of the items in <var>shapeB</var>.</p>
      <li data-md>
       <p>If <var>shapeA</var>[1] is not equal to <var>shapeB</var>[0], then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⑦②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⓪⑦">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c③">c</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists②⑤">exists</a>:</p>
+      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c④">c</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists②⑤">exists</a>:</p>
       <ol>
        <li data-md>
         <p>If it is not <a data-link-type="dfn" href="#unidirectionally-broadcastable" id="ref-for-unidirectionally-broadcastable④">unidirectionally broadcastable</a> to the shape « <var>shapeA</var>[0], <var>shapeB</var>[1] », then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw①⑦③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⓪⑧">TypeError</a></code>.</p>
@@ -5507,7 +5507,7 @@ <h4 class="heading settled" data-level="7.9.19" id="api-mlgraphbuilder-gemm"><sp
        <li data-md>
         <p>Set <var>operator</var>’s <a data-link-type="dfn" href="#operator-input" id="ref-for-operator-input②⓪">inputs</a> to <var>a</var> and <var>b</var>.</p>
        <li data-md>
-        <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c④">c</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists②⑥">exists</a>, then add it to <var>operator</var>’s <a data-link-type="dfn" href="#operator-input" id="ref-for-operator-input②①">inputs</a>.</p>
+        <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgemmoptions-c" id="ref-for-dom-mlgemmoptions-c⑤">c</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists②⑥">exists</a>, then add it to <var>operator</var>’s <a data-link-type="dfn" href="#operator-input" id="ref-for-operator-input②①">inputs</a>.</p>
        <li data-md>
         <p>Set <var>operator</var>’s <a data-link-type="dfn" href="#operator-output" id="ref-for-operator-output①④">output</a> to <var>output</var>.</p>
       </ol>
@@ -5594,10 +5594,10 @@ <h4 class="heading settled" data-level="7.9.20" id="api-mlgraphbuilder-gru"><spa
    <dl>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruOptions" data-dfn-type="dict-member" data-export id="dom-mlgruoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①⓪">MLOperand</a></span>
     <dd data-md>
-     <p>The 2-D input bias tensor of shape <em>[numDirections, 3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout①">layout</a></code> argument.</p>
+     <p>The 2-D input bias tensor of shape <em>[numDirections, 3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout①">layout</a></code>.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruOptions" data-dfn-type="dict-member" data-export id="dom-mlgruoptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①①">MLOperand</a></span>
     <dd data-md>
-     <p>The 2-D recurrent bias tensor of shape <em>[numDirections, 3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout②">layout</a></code> argument.</p>
+     <p>The 2-D recurrent bias tensor of shape <em>[numDirections, 3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout②">layout</a></code>.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruOptions" data-dfn-type="dict-member" data-export id="dom-mlgruoptions-initialhiddenstate"><code>initialHiddenState</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②①②">MLOperand</a></span>
     <dd data-md>
      <p>The 3-D initial hidden state tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>.
@@ -5624,9 +5624,9 @@ <h4 class="heading settled" data-level="7.9.20" id="api-mlgraphbuilder-gru"><spa
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①③">MLOperand</a></code>. The input 3-D tensor of shape <em>[steps, batchSize, inputSize]</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①④">MLOperand</a></code>. The 3-D input weight tensor of shape <em>[numDirections, 3 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout③">layout</a></code> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①④">MLOperand</a></code>. The 3-D input weight tensor of shape <em>[numDirections, 3 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout③">layout</a></code>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①⑤">MLOperand</a></code>. The 3-D recurrent weight tensor of shape <em>[numDirections, 3 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout④">layout</a></code> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①⑤">MLOperand</a></code>. The 3-D recurrent weight tensor of shape <em>[numDirections, 3 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout④">layout</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-steps"><code>steps</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long②⑨">unsigned long</a></code> scalar. The number of time steps in the recurrent network. The value must be greater than 0.</p>
      <li data-md>
@@ -5634,7 +5634,7 @@ <h4 class="heading settled" data-level="7.9.20" id="api-mlgraphbuilder-gru"><spa
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gru(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-gru-input-weight-recurrentweight-steps-hiddensize-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlgruoptions" id="ref-for-dictdef-mlgruoptions②">MLGruOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⑥">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①⑥">MLOperand</a></code>>. The first element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the cell output from the last time step of the network. Additionally, if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-returnsequence" id="ref-for-dom-mlgruoptions-returnsequence①">returnSequence</a></code> is set to true, the second element is the 4-D output tensor of shape <em>[steps, numDirections, batchSize, hiddenSize]</em> containing every cell outputs from each time step in the temporal sequence.</p>
+    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence①⑥">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②①⑥">MLOperand</a></code>>. The first element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the cell output from the last time step of the network. Additionally, if <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-returnsequence" id="ref-for-dom-mlgruoptions-returnsequence①">returnSequence</a></code> is set to true, the second element is the 4-D output tensor of shape <em>[steps, numDirections, batchSize, hiddenSize]</em> containing every cell outputs from each time step in the temporal sequence.</p>
    </div>
    <table class="data" id="constraints-gru">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-gru" id="ref-for-dom-mlgraphbuilder-gru①">gru()</a></code></caption>
@@ -5987,10 +5987,10 @@ <h4 class="heading settled" data-level="7.9.21" id="api-mlgraphbuilder-grucell">
    <dl>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruCellOptions" data-dfn-type="dict-member" data-export id="dom-mlgrucelloptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②④">MLOperand</a></span>
     <dd data-md>
-     <p>The 1-D input bias tensor of shape <em>[3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout⑤">layout</a></code> argument.</p>
+     <p>The 1-D input bias tensor of shape <em>[3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout⑤">layout</a></code>.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruCellOptions" data-dfn-type="dict-member" data-export id="dom-mlgrucelloptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②②⑤">MLOperand</a></span>
     <dd data-md>
-     <p>The 1-D recurrent bias tensor of shape <em>[3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout⑥">layout</a></code> argument.</p>
+     <p>The 1-D recurrent bias tensor of shape <em>[3 * hiddenSize]</em>. The ordering of the bias vectors in the second dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mlgruoptions-layout" id="ref-for-dom-mlgruoptions-layout⑥">layout</a></code>.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLGruCellOptions" data-dfn-type="dict-member" data-export id="dom-mlgrucelloptions-resetafter"><code>resetAfter</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean②⓪">boolean</a>, defaulting to <code>true</code></span>
     <dd data-md>
      <p>Indicates whether to apply the reset gate after or before matrix multiplication.</p>
@@ -6007,9 +6007,9 @@ <h4 class="heading settled" data-level="7.9.21" id="api-mlgraphbuilder-grucell">
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑥">MLOperand</a></code>. The input 2-D tensor of shape <em>[batchSize, inputSize]</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑦">MLOperand</a></code>. The 2-D input weight tensor of shape <em>[3 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑦">MLOperand</a></code>. The 2-D input weight tensor of shape <em>[3 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mlgrucelloptions-layout" id="ref-for-dom-mlgrucelloptions-layout①">layout</a></code>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑧">MLOperand</a></code>. The 2-D recurrent weight tensor of shape <em>[3 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑧">MLOperand</a></code>. The 2-D recurrent weight tensor of shape <em>[3 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mlgrucelloptions-layout" id="ref-for-dom-mlgrucelloptions-layout②">layout</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/gruCell(input, weight, recurrentWeight, hiddenState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-grucell-input-weight-recurrentweight-hiddenstate-hiddensize-options-hiddenstate"><code>hiddenState</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②②⑨">MLOperand</a></code>. The 2-D input hidden state tensor of shape <em>[batchSize, hiddenSize]</em>.</p>
      <li data-md>
@@ -6300,7 +6300,7 @@ <h4 class="heading settled" data-level="7.9.22" id="api-mlgraphbuilder-hard-sigm
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③④">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③④">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardsigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-hardSigmoid">
@@ -6312,13 +6312,13 @@ <h4 class="heading settled" data-level="7.9.22" id="api-mlgraphbuilder-hard-sigm
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks②⑤">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardsigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardsigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32②④">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16②②">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①⑤">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as③⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardsigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardsigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as③⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardsigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardsigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-hardsigmoid-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits③⑧">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardsigmoid" id="ref-for-dom-mlgraphbuilder-hardsigmoid②">hardSigmoid()</a></code>:</p>
    <dl>
@@ -6393,7 +6393,7 @@ <h4 class="heading settled" data-level="7.9.23" id="api-mlgraphbuilder-hard-swis
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③⑧">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②③⑧">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardswish-input-options-input" id="ref-for-dom-mlgraphbuilder-hardswish-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-hardSwish">
@@ -6405,13 +6405,13 @@ <h4 class="heading settled" data-level="7.9.23" id="api-mlgraphbuilder-hard-swis
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks②⑥">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardswish-input-options-input" id="ref-for-dom-mlgraphbuilder-hardswish-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardswish-input-options-input" id="ref-for-dom-mlgraphbuilder-hardswish-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32②⑤">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16②③">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①⑥">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as③⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardswish-input-options-input" id="ref-for-dom-mlgraphbuilder-hardswish-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardswish-input-options-input" id="ref-for-dom-mlgraphbuilder-hardswish-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as③⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardswish-input-options-input" id="ref-for-dom-mlgraphbuilder-hardswish-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardswish-input-options-input" id="ref-for-dom-mlgraphbuilder-hardswish-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits④⓪">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-hardswish" id="ref-for-dom-mlgraphbuilder-hardswish②">hardSwish()</a></code>:</p>
    <dl>
@@ -6492,10 +6492,10 @@ <h4 class="heading settled" data-level="7.9.24" id="api-mlgraphbuilder-instancen
    <dl>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLInstanceNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlinstancenormalizationoptions-scale"><code>scale</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④③">MLOperand</a></span>
     <dd data-md>
-     <p>The 1-D tensor of the scaling values whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size①⑨">size</a> is equal to the number of channels, i.e. the size of the feature dimension of the input. For example, for an <var>input</var> tensor with <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw⑨">"nchw"</a></code> layout, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②⓪">size</a> is equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape④⑧">shape</a>[1].</p>
+     <p>The 1-D tensor of the scaling values whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size①⑨">size</a> is equal to the number of channels, i.e. the size of the feature dimension of the input. For example, for an <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input①">input</a></code> tensor with <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw⑨">"nchw"</a></code> layout, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②⓪">size</a> is equal to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input②">input</a></code>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape④⑧">shape</a>[1].</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLInstanceNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlinstancenormalizationoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②④④">MLOperand</a></span>
     <dd data-md>
-     <p>The 1-D tensor of the bias values whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②①">size</a> is equal to the size of the feature dimension of the input. For example, for an <var>input</var> tensor with <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw①⓪">"nchw"</a></code> layout, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②②">size</a> is equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape④⑨">shape</a>[1].</p>
+     <p>The 1-D tensor of the bias values whose <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②①">size</a> is equal to the size of the feature dimension of the input. For example, for an <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input③">input</a></code> tensor with <code class="idl"><a data-link-type="idl" href="#dom-mlinputoperandlayout-nchw" id="ref-for-dom-mlinputoperandlayout-nchw①⓪">"nchw"</a></code> layout, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②②">size</a> is equal to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input④">input</a></code>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape④⑨">shape</a>[1].</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLInstanceNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mlinstancenormalizationoptions-epsilon"><code>epsilon</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double①④">double</a>, defaulting to <code>1e-5</code></span>
     <dd data-md>
      <p>A small value to prevent computational error due to divide-by-zero.</p>
@@ -6511,7 +6511,7 @@ <h4 class="heading settled" data-level="7.9.24" id="api-mlgraphbuilder-instancen
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/instanceNormalization(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-instancenormalization-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlinstancenormalizationoptions" id="ref-for-dictdef-mlinstancenormalizationoptions②">MLInstanceNormalizationOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②④⑥">MLOperand</a></code>. The instance-normalized 4-D tensor of the same shape as <em>input</em>.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②④⑥">MLOperand</a></code>. The instance-normalized 4-D tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input⑤">input</a></code>.</p>
    </div>
    <table class="data" id="constraints-instanceNormalization">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization" id="ref-for-dom-mlgraphbuilder-instancenormalization①">instanceNormalization()</a></code></caption>
@@ -6522,20 +6522,20 @@ <h4 class="heading settled" data-level="7.9.24" id="api-mlgraphbuilder-instancen
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks②⑦">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input⑥">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32②⑥">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16②④">"float16"</a></code>
       <td>4
      <tr>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mlinstancenormalizationoptions-scale" id="ref-for-dom-mlinstancenormalizationoptions-scale①">scale</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as③⑨">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input②">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as③⑨">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input⑦">input</a></code>
       <td>1
      <tr>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mlinstancenormalizationoptions-bias" id="ref-for-dom-mlinstancenormalizationoptions-bias①">bias</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input⑧">input</a></code>
       <td>1
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input④">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-instancenormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-instancenormalization-input-options-input⑨">input</a></code>
       <td>4
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlnormalizationsupportlimits" id="ref-for-dictdef-mlnormalizationsupportlimits①">MLNormalizationSupportLimits</a></code> has the following members:</p>
@@ -6660,13 +6660,13 @@ <h4 class="heading settled" data-level="7.9.25" id="api-mlgraphbuilder-layernorm
    <dl>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLayerNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mllayernormalizationoptions-scale"><code>scale</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤①">MLOperand</a></span>
     <dd data-md>
-     <p>The N-D tensor of the scaling values whose shape is determined by the <var>axes</var> member in that each value in <var>axes</var> indicates the dimension of the input tensor with scaling values. For example, for an <var>axes</var> values of [1,2,3], the shape of this tensor is the list of the corresponding sizes of the input dimension 1, 2 and 3. When this member is not present, the scaling value is assumed to be 1.</p>
+     <p>The N-D tensor of the scaling values whose shape is determined by the <code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes①">axes</a></code> member in that each value in <code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes②">axes</a></code> indicates the dimension of the input tensor with scaling values. For example, for an <code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes③">axes</a></code> values of [1,2,3], the shape of this tensor is the list of the corresponding sizes of the input dimension 1, 2 and 3. When this member is not present, the scaling value is assumed to be 1.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLayerNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mllayernormalizationoptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑤②">MLOperand</a></span>
     <dd data-md>
-     <p>The N-D tensor of the bias values whose shape is determined by the <var>axes</var> member in that each value in <var>axes</var> indicates the dimension of the input tensor with bias values. For example, for an <var>axes</var> values of [1,2,3], the shape of this tensor is the list of the corresponding sizes of the input dimension 1, 2 and 3. When this member is not present, the bias value is assumed to be 0.</p>
+     <p>The N-D tensor of the bias values whose shape is determined by the <code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes④">axes</a></code> member in that each value in <code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes⑤">axes</a></code> indicates the dimension of the input tensor with bias values. For example, for an <code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes⑥">axes</a></code> values of [1,2,3], the shape of this tensor is the list of the corresponding sizes of the input dimension 1, 2 and 3. When this member is not present, the bias value is assumed to be 0.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLayerNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mllayernormalizationoptions-axes"><code>axes</code></dfn>, <span> of type <code class="idl-code">sequence&lt;[EnforceRange] unsigned long></code></span>
     <dd data-md>
-     <p>The indices to the input dimensions to reduce. When this member is not present, it is treated as if all dimensions except the first were given (e.g. for a 4-D input tensor, axes = [1,2,3]). That is, the reduction for the mean and variance values are calculated across all the input features for each independent batch. If empty, no dimensions are reduced.</p>
+     <p>The indices to the input dimensions to reduce. When this member is not present, it is treated as if all dimensions except the first were given (e.g. for a 4-D input tensor, <code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes⑦">axes</a></code> = [1,2,3]). That is, the reduction for the mean and variance values are calculated across all the input features for each independent batch. If empty, no dimensions are reduced.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLayerNormalizationOptions" data-dfn-type="dict-member" data-export id="dom-mllayernormalizationoptions-epsilon"><code>epsilon</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-double" id="ref-for-idl-double①⑥">double</a>, defaulting to <code>1e-5</code></span>
     <dd data-md>
      <p>A small value to prevent computational error due to divide-by-zero.</p>
@@ -6679,7 +6679,7 @@ <h4 class="heading settled" data-level="7.9.25" id="api-mlgraphbuilder-layernorm
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/layerNormalization(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-layernormalization-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mllayernormalizationoptions" id="ref-for-dictdef-mllayernormalizationoptions②">MLLayerNormalizationOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤④">MLOperand</a></code>. The layer-normalized N-D tensor of the same shape as <em>input</em>.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤④">MLOperand</a></code>. The layer-normalized N-D tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input①">input</a></code>.</p>
    </div>
    <table class="data" id="constraints-layerNormalization">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization" id="ref-for-dom-mlgraphbuilder-layernormalization①">layerNormalization()</a></code></caption>
@@ -6690,21 +6690,21 @@ <h4 class="heading settled" data-level="7.9.25" id="api-mlgraphbuilder-layernorm
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks②⑨">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32②⑦">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16②⑤">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①⑦">N</a>
      <tr>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-scale" id="ref-for-dom-mllayernormalizationoptions-scale①">scale</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input②">input</a></code>
-      <td>0 to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input③">input</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③④">rank</a>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input③">input</a></code>
+      <td>0 to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input④">input</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③④">rank</a>
      <tr>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-bias" id="ref-for-dom-mllayernormalizationoptions-bias①">bias</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④③">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input④">input</a></code>
-      <td>0 to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input⑤">input</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑤">rank</a>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④③">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input⑤">input</a></code>
+      <td>0 to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input⑥">input</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑤">rank</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④④">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input⑥">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑨">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input⑦">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④④">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input⑦">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as⑨">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization-input-options-input" id="ref-for-dom-mlgraphbuilder-layernormalization-input-options-input⑧">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits④④">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-layernormalization" id="ref-for-dom-mlgraphbuilder-layernormalization②">layerNormalization()</a></code>:</p>
    <dl>
@@ -6722,9 +6722,9 @@ <h4 class="heading settled" data-level="7.9.25" id="api-mlgraphbuilder-layernorm
      <li data-md>
       <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype⑥⓪">dataType</a> is not one of its <a data-link-type="dfn" href="#allowed-data-types" id="ref-for-allowed-data-types④⑨">allowed data types</a> (according to <a href="#constraints-layerNormalization">this table</a>), then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②①⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①④⑧">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes①">axes</a></code> does not <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑤②">exist</a>, then set <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes②">axes</a></code> to a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list②①">list</a>, either equal to <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range③">the range</a> from 1 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑥">rank</a>, exclusive, if <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑦">rank</a> is greater than 1, or an empty <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list②②">list</a> otherwise.</p>
+      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes⑧">axes</a></code> does not <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑤②">exist</a>, then set <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes⑨">axes</a></code> to a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list②①">list</a>, either equal to <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range③">the range</a> from 1 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑥">rank</a>, exclusive, if <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑦">rank</a> is greater than 1, or an empty <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list②②">list</a> otherwise.</p>
      <li data-md>
-      <p>Otherwise, if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes③">axes</a></code> contains duplicate values, or if any of its elements is not in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range④">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑧">rank</a>, exclusive, then return failure.</p>
+      <p>Otherwise, if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes①⓪">axes</a></code> contains duplicate values, or if any of its elements is not in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range④">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑧">rank</a>, exclusive, then return failure.</p>
      <li data-md>
       <p>Set <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-epsilon" id="ref-for-dom-mllayernormalizationoptions-epsilon①">epsilon</a></code> to the result of <a data-link-type="dfn" href="#cast" id="ref-for-cast①①">casting</a> <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-epsilon" id="ref-for-dom-mllayernormalizationoptions-epsilon②">epsilon</a></code> to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype⑥①">dataType</a>.</p>
      <li data-md>
@@ -6733,7 +6733,7 @@ <h4 class="heading settled" data-level="7.9.25" id="api-mlgraphbuilder-layernorm
        <li data-md>
         <p>If its <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype⑥②">dataType</a> is not one of its <a data-link-type="dfn" href="#allowed-data-types" id="ref-for-allowed-data-types⑤⓪">allowed data types</a> (according to <a href="#constraints-layerNormalization">this table</a>), then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②②⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①④⑨">TypeError</a></code>.</p>
        <li data-md>
-        <p>If its <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑨">rank</a> is not equal to <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes④">axes</a></code>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②③">size</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②②①">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⑤⓪">TypeError</a></code>.</p>
+        <p>If its <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank③⑨">rank</a> is not equal to <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes①①">axes</a></code>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②③">size</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②②①">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⑤⓪">TypeError</a></code>.</p>
       </ol>
      <li data-md>
       <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-bias" id="ref-for-dom-mllayernormalizationoptions-bias③">bias</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑤④">exists</a>:</p>
@@ -6741,13 +6741,13 @@ <h4 class="heading settled" data-level="7.9.25" id="api-mlgraphbuilder-layernorm
        <li data-md>
         <p>If its <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype⑥③">dataType</a> is not one of its <a data-link-type="dfn" href="#allowed-data-types" id="ref-for-allowed-data-types⑤①">allowed data types</a> (according to <a href="#constraints-layerNormalization">this table</a>), then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②②②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⑤①">TypeError</a></code>.</p>
        <li data-md>
-        <p>If its <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⓪">rank</a> is not equal to <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes⑤">axes</a></code>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②④">size</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②②③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⑤②">TypeError</a></code>.</p>
+        <p>If its <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⓪">rank</a> is not equal to <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes①②">axes</a></code>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②④">size</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②②③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⑤②">TypeError</a></code>.</p>
       </ol>
      <li data-md>
-      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate⑨">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range⑤">the range</a> 0 to <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes⑥">axes</a></code>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②⑤">size</a>, exclusive:</p>
+      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate⑨">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range⑤">the range</a> 0 to <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes①③">axes</a></code>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size②⑤">size</a>, exclusive:</p>
       <ol>
        <li data-md>
-        <p>Let <var>axis</var> be <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes⑦">axes</a></code>[<var>index</var>].</p>
+        <p>Let <var>axis</var> be <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllayernormalizationoptions-axes" id="ref-for-dom-mllayernormalizationoptions-axes①④">axes</a></code>[<var>index</var>].</p>
        <li data-md>
         <p>If <var>axis</var> is greater or equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④①">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②②④">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror①⑤③">TypeError</a></code>.</p>
        <li data-md>
@@ -6844,7 +6844,7 @@ <h4 class="heading settled" data-level="7.9.26" id="api-mlgraphbuilder-leakyrelu
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤⑧">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑤⑧">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-leakyrelu-input-options-input" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-leakyRelu">
@@ -6856,13 +6856,13 @@ <h4 class="heading settled" data-level="7.9.26" id="api-mlgraphbuilder-leakyrelu
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks③⓪">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-leakyrelu-input-options-input" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-leakyrelu-input-options-input" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32②⑧">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16②⑥">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①⑧">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-leakyrelu-input-options-input" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-leakyrelu-input-options-input" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-leakyrelu-input-options-input" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-leakyrelu-input-options-input" id="ref-for-dom-mlgraphbuilder-leakyrelu-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits④⑥">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-leakyrelu" id="ref-for-dom-mlgraphbuilder-leakyrelu②">leakyRelu()</a></code>:</p>
    <dl>
@@ -6947,7 +6947,7 @@ <h4 class="heading settled" data-level="7.9.27" id="api-mlgraphbuilder-linear"><
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑥②">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑥②">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-linear-input-options-input" id="ref-for-dom-mlgraphbuilder-linear-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-linear">
@@ -6959,13 +6959,13 @@ <h4 class="heading settled" data-level="7.9.27" id="api-mlgraphbuilder-linear"><
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks③①">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-linear-input-options-input" id="ref-for-dom-mlgraphbuilder-linear-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-linear-input-options-input" id="ref-for-dom-mlgraphbuilder-linear-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32②⑨">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16②⑦">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank①⑨">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-linear-input-options-input" id="ref-for-dom-mlgraphbuilder-linear-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-linear-input-options-input" id="ref-for-dom-mlgraphbuilder-linear-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as④⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-linear-input-options-input" id="ref-for-dom-mlgraphbuilder-linear-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-linear-input-options-input" id="ref-for-dom-mlgraphbuilder-linear-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits④⑧">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-linear" id="ref-for-dom-mlgraphbuilder-linear②">linear()</a></code>:</p>
    <dl>
@@ -7096,9 +7096,9 @@ <h4 class="heading settled" data-level="7.9.28" id="api-mlgraphbuilder-lstm"><sp
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑦">MLOperand</a></code>. The input 3-D tensor of shape <em>[steps, batchSize, inputSize]</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑧">MLOperand</a></code>. The 3-D input weight tensor of shape <em>[numDirections, 4 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout③">layout</a></code>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑧">MLOperand</a></code>. The 3-D input weight tensor of shape <em>[numDirections, 4 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout③">layout</a></code>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑨">MLOperand</a></code>. The 3-D recurrent weight tensor of shape <em>[numDirections, 4 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to the <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout④">layout</a></code> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑦⑨">MLOperand</a></code>. The 3-D recurrent weight tensor of shape <em>[numDirections, 4 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the second dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-layout" id="ref-for-dom-mllstmoptions-layout④">layout</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-steps"><code>steps</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long③⑥">unsigned long</a></code> scalar. The number of time steps in the recurrent network. The value must be greater than 0.</p>
      <li data-md>
@@ -7106,7 +7106,7 @@ <h4 class="heading settled" data-level="7.9.28" id="api-mlgraphbuilder-lstm"><sp
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstm(input, weight, recurrentWeight, steps, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstm-input-weight-recurrentweight-steps-hiddensize-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mllstmoptions" id="ref-for-dictdef-mllstmoptions②">MLLstmOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②①">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑧⓪">MLOperand</a></code>>. The first element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the output hidden state from the last time step of the network. The second element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the output cell state from the last time step of the network. Additionally, if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-returnsequence" id="ref-for-dom-mllstmoptions-returnsequence①">returnSequence</a></code> is set to true, the third element is the 4-D output tensor of shape <em>[steps, numDirections, batchSize, hiddenSize]</em> containing every output from each time step in the temporal sequence.</p>
+    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②①">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑧⓪">MLOperand</a></code>>. The first element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the output hidden state from the last time step of the network. The second element is a 3-D tensor of shape <em>[numDirections, batchSize, hiddenSize]</em>, the output cell state from the last time step of the network. Additionally, if <code class="idl"><a data-link-type="idl" href="#dom-mllstmoptions-returnsequence" id="ref-for-dom-mllstmoptions-returnsequence①">returnSequence</a></code> is set to true, the third element is the 4-D output tensor of shape <em>[steps, numDirections, batchSize, hiddenSize]</em> containing every output from each time step in the temporal sequence.</p>
    </div>
    <table class="data" id="constraints-lstm">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-lstm" id="ref-for-dom-mlgraphbuilder-lstm①">lstm()</a></code></caption>
@@ -7534,10 +7534,10 @@ <h4 class="heading settled" data-level="7.9.29" id="api-mlgraphbuilder-lstmcell"
    <dl>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-bias"><code>bias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨⓪">MLOperand</a></span>
     <dd data-md>
-     <p>The 1-D input bias tensor of shape <em>[4 * hiddenSize]</em>. The ordering of the bias vectors in the first dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mllstmcelloptions-layout" id="ref-for-dom-mllstmcelloptions-layout①">layout</a></code> argument.</p>
+     <p>The 1-D input bias tensor of shape <em>[4 * hiddenSize]</em>. The ordering of the bias vectors in the first dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mllstmcelloptions-layout" id="ref-for-dom-mllstmcelloptions-layout①">layout</a></code>.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-recurrentbias"><code>recurrentBias</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨①">MLOperand</a></span>
     <dd data-md>
-     <p>The 1-D recurrent bias tensor of shape <em>[4 * hiddenSize]</em>. The ordering of the bias vectors in the first dimension of the tensor shape is specified according to the <code class="idl"><a data-link-type="idl" href="#dom-mllstmcelloptions-layout" id="ref-for-dom-mllstmcelloptions-layout②">layout</a></code> argument.</p>
+     <p>The 1-D recurrent bias tensor of shape <em>[4 * hiddenSize]</em>. The ordering of the bias vectors in the first dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mllstmcelloptions-layout" id="ref-for-dom-mllstmcelloptions-layout②">layout</a></code>.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLLstmCellOptions" data-dfn-type="dict-member" data-export id="dom-mllstmcelloptions-peepholeweight"><code>peepholeWeight</code></dfn>, <span> of type <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand②⑨②">MLOperand</a></span>
     <dd data-md>
      <p>The 1-D weight tensor for peepholes of shape <em>[3 * hiddenSize]</em>. The pack ordering of the weight vectors is for the <code>input (i)</code>, <code>output (o)</code>, and <code>forget (f)</code> gate, respectively.</p>
@@ -7554,9 +7554,9 @@ <h4 class="heading settled" data-level="7.9.29" id="api-mlgraphbuilder-lstmcell"
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨③">MLOperand</a></code>. The input 2-D tensor of shape <em>[batchSize, inputSize]</em>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨④">MLOperand</a></code>. The 2-D input weight tensor of shape <em>[4 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-weight"><code>weight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨④">MLOperand</a></code>. The 2-D input weight tensor of shape <em>[4 * hiddenSize, inputSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mllstmcelloptions-layout" id="ref-for-dom-mllstmcelloptions-layout③">layout</a></code>.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨⑤">MLOperand</a></code>. The 2-D recurrent weight tensor of shape <em>[4 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to the <em>options.layout</em> argument.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-recurrentweight"><code>recurrentWeight</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨⑤">MLOperand</a></code>. The 2-D recurrent weight tensor of shape <em>[4 * hiddenSize, hiddenSize]</em>. The ordering of the weight vectors in the first dimension of the tensor shape is specified according to <code class="idl"><a data-link-type="idl" href="#dom-mllstmcelloptions-layout" id="ref-for-dom-mllstmcelloptions-layout④">layout</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/lstmCell(input, weight, recurrentWeight, hiddenState, cellState, hiddenSize, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-lstmcell-input-weight-recurrentweight-hiddenstate-cellstate-hiddensize-options-hiddenstate"><code>hiddenState</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand②⑨⑥">MLOperand</a></code>. The 2-D input hidden state tensor of shape <em>[batchSize, hiddenSize]</em>.</p>
      <li data-md>
@@ -7905,10 +7905,10 @@ <h4 class="heading settled" data-level="7.9.30" id="api-mlgraphbuilder-matmul"><
      Computes the matrix product of two input tensors as follows: 
     <ul>
      <li data-md>
-      <p>If both <em>a</em> and <em>b</em> are 2-dimensional, they are multiplied like conventional
+      <p>If both <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a①">a</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-b" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-b①">b</a></code> are 2-dimensional, they are multiplied like conventional
 matrices and produce a 2-dimensional tensor as the output.</p>
      <li data-md>
-      <p>If either <em>a</em> or <em>b</em> is <code>N</code>-dimensional where <code>N > 2</code>, it is treated as a stack of matrices with dimensions corresponding to the last two indices. The matrix multiplication will be <a data-link-type="dfn" href="#broadcasting" id="ref-for-broadcasting②">broadcast</a> according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>. The shapes of <em>a</em> and <em>b</em>, except the last two dimensions, must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable③">bidirectionally broadcastable</a>. The output is a <code>N</code>-dimensional tensor whose rank is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④④">rank</a> of the input tensors. For each dimension, except the last two, of the output tensor, its size is the maximum size along that dimension of the input tensors.</p>
+      <p>If either <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a②">a</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-b" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-b②">b</a></code> is <code>N</code>-dimensional where <code>N > 2</code>, it is treated as a stack of matrices with dimensions corresponding to the last two indices. The matrix multiplication will be <a data-link-type="dfn" href="#broadcasting" id="ref-for-broadcasting②">broadcast</a> according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>. The shapes of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a③">a</a></code> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-b" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-b③">b</a></code>, except the last two dimensions, must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable③">bidirectionally broadcastable</a>. The output is a <code>N</code>-dimensional tensor whose rank is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④④">rank</a> of the input tensors. For each dimension, except the last two, of the output tensor, its size is the maximum size along that dimension of the input tensors.</p>
     </ul>
    </div>
    <table class="data" id="constraints-matmul">
@@ -7920,17 +7920,17 @@ <h4 class="heading settled" data-level="7.9.30" id="api-mlgraphbuilder-matmul"><
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks③⑥">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a①">a</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a④">a</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32③②">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16③⓪">"float16"</a></code>
       <td>2 or greater
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-b" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-b①">b</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑥⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a②">a</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-b" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-b④">b</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑥⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a⑤">a</a></code>
       <td>2 or greater
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑥⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a③">a</a></code>
-      <td>maximum of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a④">a</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑤">rank</a> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-b" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-b②">b</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑥">rank</a>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑥⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a⑥">a</a></code>
+      <td>maximum of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-a" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-a⑦">a</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑤">rank</a> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul-a-b-options-b" id="ref-for-dom-mlgraphbuilder-matmul-a-b-options-b⑤">b</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑥">rank</a>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑤④">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-matmul" id="ref-for-dom-mlgraphbuilder-matmul②">matmul()</a></code>:</p>
    <dl>
@@ -8048,9 +8048,9 @@ <h4 class="heading settled" data-level="7.9.31" id="api-mlgraphbuilder-pad"><spa
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⓪⑨">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-beginningpadding"><code>beginningPadding</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⑦">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④②">unsigned long</a></code>>. The number of padding values to add at the beginning of each input dimension, of length <em>N</em> where <em>N</em> is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑨">rank</a> of the input tensor. For each dimension <em>d</em> of <em>input</em>, <em>beginningPadding[d]</em> indicates how many values to add before the content in that dimension.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-beginningpadding"><code>beginningPadding</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⑦">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④②">unsigned long</a></code>>. The number of padding values to add at the beginning of each input dimension, of length <em>N</em> where <em>N</em> is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑨">rank</a> of the input tensor. For each dimension <em>d</em> of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input①">input</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-beginningpadding" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-beginningpadding①">beginningPadding</a></code>[<em>d</em>] indicates how many values to add before the content in that dimension.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-endingpadding"><code>endingPadding</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⑧">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④③">unsigned long</a></code>>. The number of padding values to add at the ending of each input dimension, of length <em>N</em> where <em>N</em> is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⓪">rank</a> of the input tensor. For each dimension <em>d</em> of <em>input</em>, <em>endingPadding[d]</em> indicates how many values to add after the content in that dimension.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-endingpadding"><code>endingPadding</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence②⑧">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④③">unsigned long</a></code>>. The number of padding values to add at the ending of each input dimension, of length <em>N</em> where <em>N</em> is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⓪">rank</a> of the input tensor. For each dimension <em>d</em> of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input②">input</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-endingpadding" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-endingpadding①">endingPadding</a></code>[<em>d</em>] indicates how many values to add after the content in that dimension.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/pad(input, beginningPadding, endingPadding, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlpadoptions" id="ref-for-dictdef-mlpadoptions②">MLPadOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
@@ -8066,13 +8066,13 @@ <h4 class="heading settled" data-level="7.9.31" id="api-mlgraphbuilder-pad"><spa
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks③⑦">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input③">input</a></code>
       <td><a data-link-type="dfn" href="#any-data-type" id="ref-for-any-data-type⑦">any</a>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank②⓪">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑥⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑥⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input④">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input" id="ref-for-dom-mlgraphbuilder-pad-input-beginningpadding-endingpadding-options-input⑤">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑤⑥">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-pad" id="ref-for-dom-mlgraphbuilder-pad②">pad()</a></code>:</p>
    <dl>
@@ -8262,15 +8262,15 @@ <h4 class="heading settled" data-level="7.9.32" id="api-mlgraphbuilder-pool2d"><
     <ul>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/averagePool2d(input, options), MLGraphBuilder/l2Pool2d(input, options), MLGraphBuilder/maxPool2d(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-averagepool2d-input-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①⑦">MLOperand</a></code>. The input 4-D tensor. The logical shape
-is interpreted according to the value of <em>options.layout</em>.</p>
+is interpreted according to the value of <code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-layout" id="ref-for-dom-mlpool2doptions-layout①">layout</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/averagePool2d(input, options), MLGraphBuilder/l2Pool2d(input, options), MLGraphBuilder/maxPool2d(input, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-averagepool2d-input-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlpool2doptions" id="ref-for-dictdef-mlpool2doptions④">MLPool2dOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③①⑧">MLOperand</a></code>. The output 4-D tensor that contains the
     result of the reduction. The logical shape is interpreted according to the
-    value of <em>layout</em>. More specifically, if the <em>options.roundingType</em> is <code class="idl"><a data-link-type="idl" href="#dom-mlroundingtype-floor" id="ref-for-dom-mlroundingtype-floor">"floor"</a></code>, the spatial dimensions of the output tensor can be calculated as follows:</p>
+    value of <code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-layout" id="ref-for-dom-mlpool2doptions-layout②">layout</a></code>. More specifically, if the <code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-roundingtype" id="ref-for-dom-mlpool2doptions-roundingtype②">roundingType</a></code> is <code class="idl"><a data-link-type="idl" href="#dom-mlroundingtype-floor" id="ref-for-dom-mlroundingtype-floor">"floor"</a></code>, the spatial dimensions of the output tensor can be calculated as follows:</p>
     <p><code>output size = floor(1 + (input size - filter size + beginning padding + ending padding) / stride)</code></p>
-    <p>or if <em>options.roundingType</em> is <code class="idl"><a data-link-type="idl" href="#dom-mlroundingtype-ceil" id="ref-for-dom-mlroundingtype-ceil">"ceil"</a></code>:</p>
+    <p>or if <code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-roundingtype" id="ref-for-dom-mlpool2doptions-roundingtype③">roundingType</a></code> is <code class="idl"><a data-link-type="idl" href="#dom-mlroundingtype-ceil" id="ref-for-dom-mlroundingtype-ceil">"ceil"</a></code>:</p>
     <p><code>output size = ceil(1 + (input size - filter size + beginning padding + ending padding) / stride)</code></p>
    </div>
    <table class="data" id="constraints-pooling">
@@ -8407,7 +8407,7 @@ <h4 class="heading settled" data-level="7.9.32" id="api-mlgraphbuilder-pool2d"><
      <li data-md>
       <p>Let <var>desc</var> be a copy of <var>input</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperand-descriptor-slot" id="ref-for-dom-mloperand-descriptor-slot⑨">[[descriptor]]</a></code>.</p>
      <li data-md>
-      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#mlgraphbuilder-calculate-pool2d-output-sizes" id="ref-for-mlgraphbuilder-calculate-pool2d-output-sizes">calculating pool2d output sizes</a> given <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-layout" id="ref-for-dom-mlpool2doptions-layout①">layout</a></code>, <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑦⑨">shape</a>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-roundingtype" id="ref-for-dom-mlpool2doptions-roundingtype②">roundingType</a></code>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-windowdimensions" id="ref-for-dom-mlpool2doptions-windowdimensions④">windowDimensions</a></code>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-padding" id="ref-for-dom-mlpool2doptions-padding④">padding</a></code>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-strides" id="ref-for-dom-mlpool2doptions-strides⑥">strides</a></code>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-dilations" id="ref-for-dom-mlpool2doptions-dilations⑤">dilations</a></code>, and <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-outputsizes" id="ref-for-dom-mlpool2doptions-outputsizes③">outputSizes</a></code> (if it <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨①">exists</a>).</p>
+      <p>Let <var>outputShape</var> be the result of <a data-link-type="dfn" href="#mlgraphbuilder-calculate-pool2d-output-sizes" id="ref-for-mlgraphbuilder-calculate-pool2d-output-sizes">calculating pool2d output sizes</a> given <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-layout" id="ref-for-dom-mlpool2doptions-layout③">layout</a></code>, <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑦⑨">shape</a>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-roundingtype" id="ref-for-dom-mlpool2doptions-roundingtype④">roundingType</a></code>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-windowdimensions" id="ref-for-dom-mlpool2doptions-windowdimensions④">windowDimensions</a></code>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-padding" id="ref-for-dom-mlpool2doptions-padding④">padding</a></code>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-strides" id="ref-for-dom-mlpool2doptions-strides⑥">strides</a></code>, <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-dilations" id="ref-for-dom-mlpool2doptions-dilations⑤">dilations</a></code>, and <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlpool2doptions-outputsizes" id="ref-for-dom-mlpool2doptions-outputsizes③">outputSizes</a></code> (if it <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨①">exists</a>).</p>
      <li data-md>
       <p>If any <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-item" id="ref-for-list-item⑧">item</a> in <var>outputShape</var> is not a <a data-link-type="dfn" href="#valid-dimension" id="ref-for-valid-dimension①③">valid dimension</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw②⑨②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②①③">TypeError</a></code>.</p>
      <li data-md>
@@ -8503,14 +8503,14 @@ <h4 class="heading settled" data-level="7.9.33" id="api-mlgraphbuilder-prelu"><s
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/prelu(input, slope, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-prelu-input-slope-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②③">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/prelu(input, slope, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-prelu-input-slope-options-slope"><code>slope</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②④">MLOperand</a></code>. The slope tensor. Its shape must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable⑤">bidirectionally broadcastable</a> to the shape of <em>input</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/prelu(input, slope, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-prelu-input-slope-options-slope"><code>slope</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②④">MLOperand</a></code>. The slope tensor. Its shape must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable⑤">bidirectionally broadcastable</a> to the shape of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input①">input</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/prelu(input, slope, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-prelu-input-slope-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥④">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②⑤">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③②⑤">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input②">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-prelu">
@@ -8522,17 +8522,17 @@ <h4 class="heading settled" data-level="7.9.33" id="api-mlgraphbuilder-prelu"><s
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks③⑨">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input③">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32③⑤">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16③③">"float16"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32⑥">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8⑥">"int8"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank②①">N</a>
      <tr>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-slope" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-slope①">slope</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input②">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input④">input</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank②②">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input③">input</a></code>
-      <td>maximum of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input④">input</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑦">rank</a> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-slope" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-slope②">slope</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑧">rank</a>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input⑤">input</a></code>
+      <td>maximum of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-input" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-input⑥">input</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑦">rank</a> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-prelu-input-slope-options-slope" id="ref-for-dom-mlgraphbuilder-prelu-input-slope-options-slope②">slope</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑧">rank</a>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlprelusupportlimits" id="ref-for-dictdef-mlprelusupportlimits①">MLPreluSupportLimits</a></code> has the following members:</p>
    <dl>
@@ -8600,7 +8600,7 @@ <h4 class="heading settled" data-level="7.9.33" id="api-mlgraphbuilder-prelu"><s
     </details>
    </div>
    <h4 class="heading settled" data-level="7.9.34" id="api-mlgraphbuilder-reduce"><span class="secno">7.9.34. </span><span class="content">Reduction operations</span><a class="self-link" href="#api-mlgraphbuilder-reduce"></a></h4>
-    Reduce the input tensor along all dimensions, or along the axes specified in the <code class="idl"><a data-link-type="idl" href="#dom-mlreduceoptions-axes" id="ref-for-dom-mlreduceoptions-axes">axes</a></code> array parameter. For each specified axis, the dimension with that index is reduced, i.e. the resulting tensor will not contain it, unless the <code class="idl"><a data-link-type="idl" href="#dom-mlreduceoptions-keepdimensions" id="ref-for-dom-mlreduceoptions-keepdimensions">keepDimensions</a></code> option is specified. The values of the resulting tensor are calculated using the specified reduction function that takes as parameters all the input values across the reduced dimensions. 
+    Reduce the input tensor along all dimensions, or along the axes specified in the <code class="idl"><a data-link-type="idl" href="#dom-mlreduceoptions-axes" id="ref-for-dom-mlreduceoptions-axes">axes</a></code> array parameter. For each specified axis, the dimension with that index is reduced, i.e. the resulting tensor will not contain it, unless <code class="idl"><a data-link-type="idl" href="#dom-mlreduceoptions-keepdimensions" id="ref-for-dom-mlreduceoptions-keepdimensions">keepDimensions</a></code> is specified. The values of the resulting tensor are calculated using the specified reduction function that takes as parameters all the input values across the reduced dimensions. 
 <pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mlreduceoptions"><code><c- g>MLReduceOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑥⑤"><c- n>MLOperatorOptions</c-></a> {
   <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③④"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange③①"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long④⑨"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mlreduceoptions-axes" id="ref-for-dom-mlreduceoptions-axes①"><c- g>axes</c-></a>;
   <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-boolean" id="ref-for-idl-boolean②③"><c- b>boolean</c-></a> <a class="idl-code" data-default="false" data-link-type="dict-member" data-type="boolean" href="#dom-mlreduceoptions-keepdimensions" id="ref-for-dom-mlreduceoptions-keepdimensions①"><c- g>keepDimensions</c-></a> = <c- b>false</c->;
@@ -8971,7 +8971,7 @@ <h4 class="heading settled" data-level="7.9.35" id="api-mlgraphbuilder-relu-meth
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤②">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑤②">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-relu-input-options-input" id="ref-for-dom-mlgraphbuilder-relu-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-relu">
@@ -8983,13 +8983,13 @@ <h4 class="heading settled" data-level="7.9.35" id="api-mlgraphbuilder-relu-meth
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks④①">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-relu-input-options-input" id="ref-for-dom-mlgraphbuilder-relu-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-relu-input-options-input" id="ref-for-dom-mlgraphbuilder-relu-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④④">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④②">"float16"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int32" id="ref-for-dom-mloperanddatatype-int32①①">"int32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-int8" id="ref-for-dom-mloperanddatatype-int8⑦">"int8"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank②④">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦③">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-relu-input-options-input" id="ref-for-dom-mlgraphbuilder-relu-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①③">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-relu-input-options-input" id="ref-for-dom-mlgraphbuilder-relu-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦③">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-relu-input-options-input" id="ref-for-dom-mlgraphbuilder-relu-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①③">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-relu-input-options-input" id="ref-for-dom-mlgraphbuilder-relu-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑥④">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-relu" id="ref-for-dom-mlgraphbuilder-relu③">relu()</a></code>:</p>
    <dl>
@@ -9078,7 +9078,7 @@ <h4 class="heading settled" data-level="7.9.36" id="api-mlgraphbuilder-resample2
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLResample2dOptions" data-dfn-type="dict-member" data-export id="dom-mlresample2doptions-sizes"><code>sizes</code></dfn>, <span> of type <code class="idl-code">sequence&lt;[EnforceRange] unsigned long></code></span>
     <dd data-md>
      <p>A list of length 2.
-Specifies the target sizes for each input dimension from <code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes②">axes</a></code>: <em>[sizeForFirstAxis, sizeForSecondAxis]</em>. When the target sizes are specified, the <code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-scales" id="ref-for-dom-mlresample2doptions-scales①">scales</a></code> argument is ignored, since the scaling factor values are derived from the target sizes of the input.</p>
+Specifies the target sizes for each input dimension from <code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes②">axes</a></code>: <em>[sizeForFirstAxis, sizeForSecondAxis]</em>. When <code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-sizes" id="ref-for-dom-mlresample2doptions-sizes①">sizes</a></code> is specified, <code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-scales" id="ref-for-dom-mlresample2doptions-scales①">scales</a></code> is ignored, since the scaling factor values are derived from the target sizes of the input.</p>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLResample2dOptions" data-dfn-type="dict-member" data-export id="dom-mlresample2doptions-axes"><code>axes</code></dfn>, <span> of type <code class="idl-code">sequence&lt;[EnforceRange] unsigned long></code></span>
     <dd data-md>
      <p>A list of length 2.
@@ -9116,7 +9116,7 @@ <h4 class="heading settled" data-level="7.9.36" id="api-mlgraphbuilder-resample2
      <li data-md>
       <p>Otherwise, if any of its values is not greater than 0, or if its <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑥">size</a> is not 2, return false.</p>
      <li data-md>
-      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-sizes" id="ref-for-dom-mlresample2doptions-sizes①">sizes</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨④">exists</a>, and if its size is not 2, or if any of its values is not greater than 0, return false.</p>
+      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-sizes" id="ref-for-dom-mlresample2doptions-sizes②">sizes</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨④">exists</a>, and if its size is not 2, or if any of its values is not greater than 0, return false.</p>
      <li data-md>
       <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes③">axes</a></code> does not <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨⑤">exists</a>, set it to the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④④">list</a> « 2, 3 ».</p>
      <li data-md>
@@ -9136,7 +9136,7 @@ <h4 class="heading settled" data-level="7.9.36" id="api-mlgraphbuilder-resample2
       <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①③">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①①">the range</a> 0 to <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes⑤">axes</a></code>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑦">size</a>, exclusive:</p>
       <ol>
        <li data-md>
-        <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-sizes" id="ref-for-dom-mlresample2doptions-sizes②">sizes</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨⑥">exists</a>, then let <var>size</var> be <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-sizes" id="ref-for-dom-mlresample2doptions-sizes③">sizes</a></code>[<var>index</var>].</p>
+        <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-sizes" id="ref-for-dom-mlresample2doptions-sizes③">sizes</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨⑥">exists</a>, then let <var>size</var> be <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-sizes" id="ref-for-dom-mlresample2doptions-sizes④">sizes</a></code>[<var>index</var>].</p>
        <li data-md>
         <p>Otherwise, let <var>size</var> be floor(<var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑧③">shape</a>[<var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes⑥">axes</a></code>[<var>index</var>]] * <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-scales" id="ref-for-dom-mlresample2doptions-scales③">scales</a></code>[<var>index</var>]).</p>
        <li data-md>
@@ -9200,14 +9200,14 @@ <h4 class="heading settled" data-level="7.9.37" id="api-mlgraphbuilder-reshape-m
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reshape(input, newShape, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reshape-input-newshape-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥⓪">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reshape(input, newShape, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reshape-input-newshape-options-newshape"><code>newShape</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence③⑨">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤③">unsigned long</a></code>>. The shape of the output tensor.
-The number of elements implied by <em>newShape</em> must be the same as the
+The number of elements implied by <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-reshape-input-newshape-options-newshape" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-options-newshape①">newShape</a></code> must be the same as the
 number of elements in the input tensor.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/reshape(input, newShape, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-reshape-input-newshape-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦⓪">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
     <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥①">MLOperand</a></code>. The output tensor. The values of the output
     tensor are the same as values of the input tensor. The shape of the output
-    tensor is specified by the <em>newShape</em> argument.</p>
+    tensor is specified by <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-reshape-input-newshape-options-newshape" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-options-newshape②">newShape</a></code>.</p>
    </div>
    <table class="data" id="constraints-reshape">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-reshape" id="ref-for-dom-mlgraphbuilder-reshape①">reshape()</a></code></caption>
@@ -9224,7 +9224,7 @@ <h4 class="heading settled" data-level="7.9.37" id="api-mlgraphbuilder-reshape-m
      <tr>
       <td><em>output</em>
       <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-reshape-input-newshape-options-input" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-options-input②">input</a></code>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-reshape-input-newshape-options-newshape" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-options-newshape①">newShape</a></code>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑧">size</a>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-reshape-input-newshape-options-newshape" id="ref-for-dom-mlgraphbuilder-reshape-input-newshape-options-newshape③">newShape</a></code>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑧">size</a>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑥⑧">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-reshape" id="ref-for-dom-mlgraphbuilder-reshape②">reshape()</a></code>:</p>
    <dl>
@@ -9292,7 +9292,7 @@ <h4 class="heading settled" data-level="7.9.38" id="api-mlgraphbuilder-sigmoid-m
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥⑤">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥⑤">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-sigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-sigmoid-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-sigmoid">
@@ -9304,13 +9304,13 @@ <h4 class="heading settled" data-level="7.9.38" id="api-mlgraphbuilder-sigmoid-m
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks④⑤">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-sigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-sigmoid-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-sigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-sigmoid-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④⑥">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④④">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank②⑥">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-sigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-sigmoid-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①④">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-sigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-sigmoid-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-sigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-sigmoid-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①④">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-sigmoid-input-options-input" id="ref-for-dom-mlgraphbuilder-sigmoid-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑦⓪">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-sigmoid" id="ref-for-dom-mlgraphbuilder-sigmoid④">sigmoid()</a></code>:</p>
    <dl>
@@ -9376,9 +9376,9 @@ <h4 class="heading settled" data-level="7.9.39" id="api-mlgraphbuilder-slice"><s
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑥⑧">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-starts"><code>starts</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④②">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑦">unsigned long</a></code>>. The starting index to slice of each input dimension, of length N where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑥③">rank</a> of the input tensor. For each dimension <em>d</em> of <em>input</em>, <em>starts[d]</em> indicates the starting index to slice in that dimension. The starting index must be in the range [0, input size - 1] in that dimension.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-starts"><code>starts</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④②">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑦">unsigned long</a></code>>. The starting index to slice of each input dimension, of length N where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑥③">rank</a> of the input tensor. For each dimension <em>d</em> of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-input①">input</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-starts" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-starts①">starts</a></code>[<em>d</em>] indicates the starting index to slice in that dimension. The starting index must be in the range [0, input size - 1] in that dimension.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-sizes"><code>sizes</code></dfn>: <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④③">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑧">unsigned long</a></code>>. The number of elements to slice of each input dimension, of length N where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑥④">rank</a> of the input tensor. For each dimension <em>d</em> of <em>input</em>, <em>sizes[d]</em> indicates the number of elements to slice in that dimension. The size must not be 0 and must satisfy the constraint <code>starting index + size &lt;= input size</code> in that dimension.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-sizes"><code>sizes</code></dfn>: a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④③">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑤⑧">unsigned long</a></code>>. The number of elements to slice of each input dimension, of length N where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑥④">rank</a> of the input tensor. For each dimension <em>d</em> of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-input②">input</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-sizes" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-sizes①">sizes</a></code>[<em>d</em>] indicates the number of elements to slice in that dimension. The size must not be 0 and must satisfy the constraint <code>starting index + size &lt;= input size</code> in that dimension.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/slice(input, starts, sizes, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-slice-input-starts-sizes-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑦④">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
@@ -9393,13 +9393,13 @@ <h4 class="heading settled" data-level="7.9.39" id="api-mlgraphbuilder-slice"><s
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks④⑥">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-input③">input</a></code>
       <td><a data-link-type="dfn" href="#any-data-type" id="ref-for-any-data-type⑨">any</a>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank②⑦">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-input④">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice-input-starts-sizes-options-input" id="ref-for-dom-mlgraphbuilder-slice-input-starts-sizes-options-input⑤">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑦②">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-slice" id="ref-for-dom-mlgraphbuilder-slice②">slice()</a></code>:</p>
    <dl>
@@ -9473,7 +9473,7 @@ <h4 class="heading settled" data-level="7.9.40" id="api-mlgraphbuilder-softmax-m
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦③">MLOperand</a></code>. The output N-D tensor that contains the softmax results, of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦③">MLOperand</a></code>. The output N-D tensor that contains the softmax results, of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softmax-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-softmax">
@@ -9485,13 +9485,13 @@ <h4 class="heading settled" data-level="7.9.40" id="api-mlgraphbuilder-softmax-m
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks④⑦">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softmax-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softmax-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④⑦">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④⑤">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank②⑧">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softmax-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softmax-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softmax-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softmax-input-axis-options-input" id="ref-for-dom-mlgraphbuilder-softmax-input-axis-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑦④">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softmax" id="ref-for-dom-mlgraphbuilder-softmax②">softmax()</a></code>:</p>
    <dl>
@@ -9566,7 +9566,7 @@ <h4 class="heading settled" data-level="7.9.41" id="api-mlgraphbuilder-softplus-
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦⑦">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑦⑦">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softplus-input-options-input" id="ref-for-dom-mlgraphbuilder-softplus-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-softplus">
@@ -9578,13 +9578,13 @@ <h4 class="heading settled" data-level="7.9.41" id="api-mlgraphbuilder-softplus-
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks④⑧">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softplus-input-options-input" id="ref-for-dom-mlgraphbuilder-softplus-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softplus-input-options-input" id="ref-for-dom-mlgraphbuilder-softplus-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④⑧">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④⑥">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank②⑨">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⑨">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softplus-input-options-input" id="ref-for-dom-mlgraphbuilder-softplus-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softplus-input-options-input" id="ref-for-dom-mlgraphbuilder-softplus-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑦⑨">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softplus-input-options-input" id="ref-for-dom-mlgraphbuilder-softplus-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑦">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softplus-input-options-input" id="ref-for-dom-mlgraphbuilder-softplus-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑦⑥">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softplus" id="ref-for-dom-mlgraphbuilder-softplus②">softplus()</a></code>:</p>
    <dl>
@@ -9661,7 +9661,7 @@ <h4 class="heading settled" data-level="7.9.42" id="api-mlgraphbuilder-softsign-
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧①">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧①">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softsign-input-options-input" id="ref-for-dom-mlgraphbuilder-softsign-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-softsign">
@@ -9673,13 +9673,13 @@ <h4 class="heading settled" data-level="7.9.42" id="api-mlgraphbuilder-softsign-
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks④⑨">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softsign-input-options-input" id="ref-for-dom-mlgraphbuilder-softsign-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softsign-input-options-input" id="ref-for-dom-mlgraphbuilder-softsign-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④⑨">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④⑦">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank③⓪">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softsign-input-options-input" id="ref-for-dom-mlgraphbuilder-softsign-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softsign-input-options-input" id="ref-for-dom-mlgraphbuilder-softsign-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softsign-input-options-input" id="ref-for-dom-mlgraphbuilder-softsign-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑧">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softsign-input-options-input" id="ref-for-dom-mlgraphbuilder-softsign-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑦⑧">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-softsign" id="ref-for-dom-mlgraphbuilder-softsign②">softsign()</a></code>:</p>
    <dl>
@@ -9742,11 +9742,11 @@ <h4 class="heading settled" data-level="7.9.43" id="api-mlgraphbuilder-split"><s
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/split(input, splits, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-split-input-splits-options-input"><code>input</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧④">MLOperand</a></code>. The input tensor.</p>
      <li data-md>
-      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/split(input, splits, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-split-input-splits-options-splits"><code>splits</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥④">unsigned long</a></code> or <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑥">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑤">unsigned long</a></code>>. If an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑥">unsigned long</a></code>, it specifies the number of output tensors along the axis. The number must evenly divide the dimension size of <em>input</em> along <em>options.axis</em>. If a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑦">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑦">unsigned long</a></code>>, it specifies the sizes of each output tensor along the <em>options.axis</em>. The sum of sizes must equal to the dimension size of <em>input</em> along <em>options.axis</em>.</p>
+      <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/split(input, splits, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-split-input-splits-options-splits"><code>splits</code></dfn>: an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥④">unsigned long</a></code> or <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑥">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑤">unsigned long</a></code>>. If an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑥">unsigned long</a></code>, it specifies the number of output tensors along the axis. The number must evenly divide the dimension size of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input①">input</a></code> along <code class="idl"><a data-link-type="idl" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis①">axis</a></code>. If a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑦">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑦">unsigned long</a></code>>, it specifies the sizes of each output tensor along the <code class="idl"><a data-link-type="idl" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis②">axis</a></code>. The sum of sizes must equal to the dimension size of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input②">input</a></code> along <code class="idl"><a data-link-type="idl" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis③">axis</a></code>.</p>
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/split(input, splits, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-split-input-splits-options-options"><code>options</code></dfn>: an optional <code class="idl"><a data-link-type="idl" href="#dictdef-mlsplitoptions" id="ref-for-dictdef-mlsplitoptions①">MLSplitOptions</a></code>. The optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑧">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧⑤">MLOperand</a></code>>. The split output tensors. If <em>splits</em> is an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑧">unsigned long</a></code>, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④②">size</a> of the output is equal to <em>splits</em>. The shape of each output tensor is the same as <em>input</em> except the dimension size of <em>axis</em> equals to the quotient of dividing the dimension size of <em>input</em> along <em>axis</em> by <em>splits</em>. If <em>splits</em> is a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑨">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑨">unsigned long</a></code>>, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④③">size</a> of the output equals the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④④">size</a> of <em>splits</em>. The shape of the i-th output tensor is the same as <em>input</em> except along <em>axis</em> where the dimension size is <em>splits[i]</em>.</p>
+    <p><strong>Returns:</strong> <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑧">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧⑤">MLOperand</a></code>>. The split output tensors. If <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-splits" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-splits①">splits</a></code> is an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑧">unsigned long</a></code>, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④②">size</a> of the output is equal to <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-splits" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-splits②">splits</a></code>. The shape of each output tensor is the same as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input③">input</a></code> except the dimension size of <code class="idl"><a data-link-type="idl" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis④">axis</a></code> equals to the quotient of dividing the dimension size of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input④">input</a></code> along <code class="idl"><a data-link-type="idl" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis⑤">axis</a></code> by <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-splits" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-splits③">splits</a></code>. If <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-splits" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-splits④">splits</a></code> is a <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④⑨">sequence</a>&lt;<code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑥⑨">unsigned long</a></code>>, the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④③">size</a> of the output equals the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④④">size</a> of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-splits" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-splits⑤">splits</a></code>. The shape of the <em>i</em>-th output tensor is the same as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input⑤">input</a></code> except along <code class="idl"><a data-link-type="idl" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis⑥">axis</a></code> where the dimension size is <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-splits" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-splits⑥">splits</a></code>[<em>i</em>].</p>
    </div>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlsplitoptions" id="ref-for-dictdef-mlsplitoptions②">MLSplitOptions</a></code> has the following members:</p>
    <dl>
@@ -9763,13 +9763,13 @@ <h4 class="heading settled" data-level="7.9.43" id="api-mlgraphbuilder-split"><s
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks⑤⓪">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input⑥">input</a></code>
       <td><a data-link-type="dfn" href="#any-data-type" id="ref-for-any-data-type①⓪">any</a>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank③①">N</a>
      <tr>
       <td><em>outputs</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑨">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧①">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input⑦">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as①⑨">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-split-input-splits-options-input" id="ref-for-dom-mlgraphbuilder-split-input-splits-options-input⑧">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlsplitsupportlimits" id="ref-for-dictdef-mlsplitsupportlimits①">MLSplitSupportLimits</a></code> has the following members:</p>
    <dl>
@@ -9794,7 +9794,7 @@ <h4 class="heading settled" data-level="7.9.43" id="api-mlgraphbuilder-split"><s
      <li data-md>
       <p>If <a data-link-type="dfn" href="#mlgraphbuilder-validate-operand" id="ref-for-mlgraphbuilder-validate-operand④⓪">validating operand</a> with <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①⑥⑥">this</a> and <var>input</var> returns false, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥①">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②④⑤">TypeError</a></code>.</p>
      <li data-md>
-      <p>Let <var>axis</var> be <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis①">axis</a></code>.</p>
+      <p>Let <var>axis</var> be <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlsplitoptions-axis" id="ref-for-dom-mlsplitoptions-axis⑦">axis</a></code>.</p>
      <li data-md>
       <p>If <var>axis</var> is greater than or equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑥⑨">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②④⑥">TypeError</a></code>.</p>
      <li data-md>
@@ -9891,7 +9891,7 @@ <h4 class="heading settled" data-level="7.9.44" id="api-mlgraphbuilder-tanh-meth
     <p><strong>Returns:</strong></p>
     <ul>
      <li data-md>
-      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧⑨">MLOperand</a></code>. The output tensor of the same shape as <em>input</em>.</p>
+      <p>an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand③⑧⑨">MLOperand</a></code>. The output tensor of the same shape as <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-tanh-input-options-input" id="ref-for-dom-mlgraphbuilder-tanh-input-options-input①">input</a></code>.</p>
     </ul>
    </div>
    <table class="data" id="constraints-tanh">
@@ -9903,13 +9903,13 @@ <h4 class="heading settled" data-level="7.9.44" id="api-mlgraphbuilder-tanh-meth
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks⑤①">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-tanh-input-options-input" id="ref-for-dom-mlgraphbuilder-tanh-input-options-input①">input</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-tanh-input-options-input" id="ref-for-dom-mlgraphbuilder-tanh-input-options-input②">input</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32⑤⓪">"float32"</a></code>, <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④⑧">"float16"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank③②">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-tanh-input-options-input" id="ref-for-dom-mlgraphbuilder-tanh-input-options-input②">input</a></code>
-      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as②⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-tanh-input-options-input" id="ref-for-dom-mlgraphbuilder-tanh-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧②">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-tanh-input-options-input" id="ref-for-dom-mlgraphbuilder-tanh-input-options-input③">input</a></code>
+      <td><a data-link-type="dfn" href="#same-rank-as" id="ref-for-same-rank-as②⓪">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-tanh-input-options-input" id="ref-for-dom-mlgraphbuilder-tanh-input-options-input④">input</a></code>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlopsupportlimits" id="ref-for-dictdef-mlopsupportlimits⑧②">MLOpSupportLimits</a></code> has the following member for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-tanh" id="ref-for-dom-mlgraphbuilder-tanh④">tanh()</a></code>:</p>
    <dl>
@@ -9960,9 +9960,9 @@ <h4 class="heading settled" data-level="7.9.44" id="api-mlgraphbuilder-tanh-meth
     </details>
    </div>
    <h4 class="heading settled" data-level="7.9.45" id="api-mlgraphbuilder-transpose"><span class="secno">7.9.45. </span><span class="content">transpose</span><a class="self-link" href="#api-mlgraphbuilder-transpose"></a></h4>
-    Permute the dimensions of the input tensor according to the <em>permutation</em> argument. 
+    Permute the dimensions of the input tensor according to <code class="idl"><a data-link-type="idl" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation">permutation</a></code>. 
 <pre class="idl highlight def"><c- b>dictionary</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="dictionary" data-export id="dictdef-mltransposeoptions"><code><c- g>MLTransposeOptions</c-></code></dfn> : <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧④"><c- n>MLOperatorOptions</c-></a> {
-  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑤①"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange④①"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑦④"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation"><c- g>permutation</c-></a>;
+  <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence⑤①"><c- b>sequence</c-></a>&lt;[<a class="idl-code" data-link-type="extended-attribute" href="https://webidl.spec.whatwg.org/#EnforceRange" id="ref-for-EnforceRange④①"><c- g>EnforceRange</c-></a>] <a class="idl-code" data-link-type="interface" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑦④"><c- b>unsigned</c-> <c- b>long</c-></a>> <a class="idl-code" data-link-type="dict-member" data-type="sequence<[EnforceRange] unsigned long>" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation①"><c- g>permutation</c-></a>;
 };
 
 <c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥③"><c- g>MLGraphBuilder</c-></a> {
@@ -10022,9 +10022,9 @@ <h4 class="heading settled" data-level="7.9.45" id="api-mlgraphbuilder-transpose
      <li data-md>
       <p>If <a data-link-type="dfn" href="#mlgraphbuilder-validate-operand" id="ref-for-mlgraphbuilder-validate-operand④②">validating operand</a> with <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①⑦⓪">this</a> and <var>input</var> returns false, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤②">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation①">permutation</a></code> does not <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨⑦">exist</a>, let <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation②">permutation</a></code> be the reversed sequence of all indices for <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑨①">shape</a>.</p>
+      <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation②">permutation</a></code> does not <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨⑦">exist</a>, let <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation③">permutation</a></code> be the reversed sequence of all indices for <var>input</var>’s <a data-link-type="dfn" href="#mloperand-shape" id="ref-for-mloperand-shape⑨①">shape</a>.</p>
      <li data-md>
-      <p>Otherwise if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation③">permutation</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨⑧">exists</a>:</p>
+      <p>Otherwise if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mltransposeoptions-permutation" id="ref-for-dom-mltransposeoptions-permutation④">permutation</a></code> <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨⑧">exists</a>:</p>
       <ol>
        <li data-md>
         <p>If its <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④⑥">size</a> is not equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑦②">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦①">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤③">TypeError</a></code>.</p>
@@ -10194,12 +10194,12 @@ <h4 class="heading settled" data-level="7.9.46" id="api-mlgraphbuilder-triangula
     </details>
    </div>
    <h4 class="heading settled" data-level="7.9.47" id="api-mlgraphbuilder-where"><span class="secno">7.9.47. </span><span class="content">where</span><a class="self-link" href="#api-mlgraphbuilder-where"></a></h4>
-    Select the values from the trueValue or the falseValue tensor depending on the corresponding values of the condition tensor, where non-zero is true and zero is false. The condition tensor is often the output of one of the element-wise logical operations. 
+    Select the values from the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue">trueValue</a></code> or the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue">falseValue</a></code> tensor depending on the corresponding values of the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition">condition</a></code> tensor, where non-zero is true and zero is false. The <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition①">condition</a></code> tensor is often the output of one of the element-wise logical operations. 
    <p>The operation will be <a data-link-type="dfn" href="#broadcasting" id="ref-for-broadcasting④">broadcast</a> according to <a data-link-type="biblio" href="#biblio-numpy-broadcasting-rule" title="General Broadcasting Rules of NumPy">[numpy-broadcasting-rule]</a>. The input tensors must be <a data-link-type="dfn" href="#bidirectionally-broadcastable" id="ref-for-bidirectionally-broadcastable⑥">bidirectionally broadcastable</a>. The <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑦⑤">rank</a> of the output tensor is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑦⑥">rank</a> of the input tensors. For each dimension of the output tensor, its size is the maximum size along that dimension of the input tensors.</p>
 <pre class="idl highlight def"><c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#mlgraphbuilder" id="ref-for-mlgraphbuilder⑥⑤"><c- g>MLGraphBuilder</c-></a> {
-  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-where" id="ref-for-dom-mlgraphbuilder-where"><c- g>where</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition"><c- g>condition</c-></a>,
-                  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④⓪⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue"><c- g>trueValue</c-></a>,
-                  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④⓪①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue"><c- g>falseValue</c-></a>,
+  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑧"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="method" href="#dom-mlgraphbuilder-where" id="ref-for-dom-mlgraphbuilder-where"><c- g>where</c-></a>(<a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑨"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition②"><c- g>condition</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④⓪⓪"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue①"><c- g>trueValue</c-></a>,
+                  <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand④⓪①"><c- n>MLOperand</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue①"><c- g>falseValue</c-></a>,
                   <c- b>optional</c-> <a data-link-type="idl-name" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧⑥"><c- n>MLOperatorOptions</c-></a> <a class="idl-code" data-link-type="argument" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-options" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-options"><c- g>options</c-></a> = {});
 };
 
@@ -10226,7 +10226,7 @@ <h4 class="heading settled" data-level="7.9.47" id="api-mlgraphbuilder-where"><s
      <li data-md>
       <p><dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder/where(condition, trueValue, falseValue, options)" data-dfn-type="argument" data-export id="dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-options"><code>options</code></dfn>: an <code class="idl"><a data-link-type="idl" href="#dictdef-mloperatoroptions" id="ref-for-dictdef-mloperatoroptions⑧⑦">MLOperatorOptions</a></code>. Specifies the optional parameters of the operation.</p>
     </ul>
-    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪⑤">MLOperand</a></code>. The output tensor that contains the values selected element-wise from either the trueValue or the falseValue tensor.</p>
+    <p><strong>Returns:</strong> an <code class="idl"><a data-link-type="idl" href="#mloperand" id="ref-for-mloperand④⓪⑤">MLOperand</a></code>. The output tensor that contains the values selected element-wise from either the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue②">trueValue</a></code> or the <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue②">falseValue</a></code> tensor.</p>
    </div>
    <table class="data" id="constraints-where">
     <caption>Constraints for <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where" id="ref-for-dom-mlgraphbuilder-where①">where()</a></code></caption>
@@ -10237,21 +10237,21 @@ <h4 class="heading settled" data-level="7.9.47" id="api-mlgraphbuilder-where"><s
       <th><a data-link-type="dfn" href="#allowed-ranks" id="ref-for-allowed-ranks⑤⑤">allowed ranks</a>
     <tbody>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition①">condition</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition③">condition</a></code>
       <td><code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-uint8" id="ref-for-dom-mloperanddatatype-uint8⑦">"uint8"</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank③④">N</a>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue①">trueValue</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue③">trueValue</a></code>
       <td><a data-link-type="dfn" href="#any-data-type" id="ref-for-any-data-type①③">any</a>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank③⑤">N</a>
      <tr>
-      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue①">falseValue</a></code>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue②">trueValue</a></code>
+      <td><code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue③">falseValue</a></code>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧⑤">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue④">trueValue</a></code>
       <td><a data-link-type="dfn" href="#any-rank" id="ref-for-any-rank③⑥">N</a>
      <tr>
       <td><em>output</em>
-      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue③">trueValue</a></code>
-      <td>maximum of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition②">condition</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑦⑦">rank</a>, <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue④">trueValue</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑦⑧">rank</a> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue②">falseValue</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑦⑨">rank</a>
+      <td><a data-link-type="dfn" href="#same-type-as" id="ref-for-same-type-as⑧⑥">same as</a> <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue⑤">trueValue</a></code>
+      <td>maximum of <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-condition④">condition</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑦⑦">rank</a>, <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-truevalue⑥">trueValue</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑦⑧">rank</a> and <code class="idl"><a data-link-type="idl" href="#dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue" id="ref-for-dom-mlgraphbuilder-where-condition-truevalue-falsevalue-options-falsevalue④">falseValue</a></code>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑦⑨">rank</a>
    </table>
    <p><code class="idl"><a data-link-type="idl" href="#dictdef-mlwheresupportlimits" id="ref-for-dictdef-mlwheresupportlimits①">MLWhereSupportLimits</a></code> has the following members:</p>
    <dl>
@@ -13163,7 +13163,7 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
 "dom-mlconv2doptions-bias": {"dfnID":"dom-mlconv2doptions-bias","dfnText":"bias","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlconv2doptions-bias"},{"id":"ref-for-dom-mlconv2doptions-bias\u2460"},{"id":"ref-for-dom-mlconv2doptions-bias\u2461"},{"id":"ref-for-dom-mlconv2doptions-bias\u2462"},{"id":"ref-for-dom-mlconv2doptions-bias\u2463"}],"title":"7.9.10. conv2d"},{"refs":[{"id":"ref-for-dom-mlconv2doptions-bias\u2464"},{"id":"ref-for-dom-mlconv2doptions-bias\u2465"}],"title":"7.9.11. convTranspose2d"}],"url":"#dom-mlconv2doptions-bias"},
 "dom-mlconv2doptions-dilations": {"dfnID":"dom-mlconv2doptions-dilations","dfnText":"dilations","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlconv2doptions-dilations"},{"id":"ref-for-dom-mlconv2doptions-dilations\u2460"},{"id":"ref-for-dom-mlconv2doptions-dilations\u2461"},{"id":"ref-for-dom-mlconv2doptions-dilations\u2462"},{"id":"ref-for-dom-mlconv2doptions-dilations\u2463"}],"title":"7.9.10. conv2d"}],"url":"#dom-mlconv2doptions-dilations"},
 "dom-mlconv2doptions-filterlayout": {"dfnID":"dom-mlconv2doptions-filterlayout","dfnText":"filterLayout","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlconv2doptions-filterlayout"},{"id":"ref-for-dom-mlconv2doptions-filterlayout\u2460"},{"id":"ref-for-dom-mlconv2doptions-filterlayout\u2461"}],"title":"7.9.10. conv2d"}],"url":"#dom-mlconv2doptions-filterlayout"},
-"dom-mlconv2doptions-groups": {"dfnID":"dom-mlconv2doptions-groups","dfnText":"groups","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlconv2doptions-groups"},{"id":"ref-for-dom-mlconv2doptions-groups\u2460"},{"id":"ref-for-dom-mlconv2doptions-groups\u2461"},{"id":"ref-for-dom-mlconv2doptions-groups\u2462"},{"id":"ref-for-dom-mlconv2doptions-groups\u2463"}],"title":"7.9.10. conv2d"}],"url":"#dom-mlconv2doptions-groups"},
+"dom-mlconv2doptions-groups": {"dfnID":"dom-mlconv2doptions-groups","dfnText":"groups","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlconv2doptions-groups"},{"id":"ref-for-dom-mlconv2doptions-groups\u2460"},{"id":"ref-for-dom-mlconv2doptions-groups\u2461"},{"id":"ref-for-dom-mlconv2doptions-groups\u2462"},{"id":"ref-for-dom-mlconv2doptions-groups\u2463"},{"id":"ref-for-dom-mlconv2doptions-groups\u2464"}],"title":"7.9.10. conv2d"}],"url":"#dom-mlconv2doptions-groups"},
 "dom-mlconv2doptions-inputlayout": {"dfnID":"dom-mlconv2doptions-inputlayout","dfnText":"inputLayout","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlconv2doptions-inputlayout"},{"id":"ref-for-dom-mlconv2doptions-inputlayout\u2460"},{"id":"ref-for-dom-mlconv2doptions-inputlayout\u2461"},{"id":"ref-for-dom-mlconv2doptions-inputlayout\u2462"},{"id":"ref-for-dom-mlconv2doptions-inputlayout\u2463"}],"title":"7.9.10. conv2d"}],"url":"#dom-mlconv2doptions-inputlayout"},
 "dom-mlconv2doptions-padding": {"dfnID":"dom-mlconv2doptions-padding","dfnText":"padding","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlconv2doptions-padding"},{"id":"ref-for-dom-mlconv2doptions-padding\u2460"},{"id":"ref-for-dom-mlconv2doptions-padding\u2461"},{"id":"ref-for-dom-mlconv2doptions-padding\u2462"}],"title":"7.9.10. conv2d"}],"url":"#dom-mlconv2doptions-padding"},
 "dom-mlconv2doptions-strides": {"dfnID":"dom-mlconv2doptions-strides","dfnText":"strides","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlconv2doptions-strides"},{"id":"ref-for-dom-mlconv2doptions-strides\u2460"},{"id":"ref-for-dom-mlconv2doptions-strides\u2461"},{"id":"ref-for-dom-mlconv2doptions-strides\u2462"},{"id":"ref-for-dom-mlconv2doptions-strides\u2463"}],"title":"7.9.10. conv2d"},{"refs":[{"id":"ref-for-dom-mlconv2doptions-strides\u2464"}],"title":"7.9.11. convTranspose2d"}],"url":"#dom-mlconv2doptions-strides"},
@@ -13187,15 +13187,15 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
 "dom-mldevicetype-gpu": {"dfnID":"dom-mldevicetype-gpu","dfnText":"gpu","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mldevicetype-gpu"}],"title":"4. Privacy Considerations"},{"refs":[{"id":"ref-for-dom-mldevicetype-gpu\u2460"}],"title":"7.2. ML interface"},{"refs":[{"id":"ref-for-dom-mldevicetype-gpu\u2461"}],"title":"7.2.2. createContext()"},{"refs":[{"id":"ref-for-dom-mldevicetype-gpu\u2462"}],"title":"7.3. MLContext interface"}],"url":"#dom-mldevicetype-gpu"},
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@@ -13475,7 +13475,7 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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