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   <title>Web Neural Network API</title>
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@@ -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="2024-08-05">5 August 2024</time></p>
+   <p id="w3c-state"><a href="https://www.w3.org/standards/types#ED">Editor’s Draft</a>, <time class="dt-updated" datetime="2024-08-22">22 August 2024</time></p>
    <details open>
     <summary>More details about this document</summary>
     <div data-fill-with="spec-metadata">
@@ -7249,7 +7249,7 @@ <h4 class="heading settled" data-level="7.7.35" id="api-mlgraphbuilder-relu-meth
     </details>
    </div>
    <h4 class="heading settled" data-level="7.7.36" id="api-mlgraphbuilder-resample2d-method"><span class="secno">7.7.36. </span><span class="content">resample2d</span><a class="self-link" href="#api-mlgraphbuilder-resample2d-method"></a></h4>
-    Resample the tensor values from the source to the destination spatial dimensions according to the scaling factors. 
+    Resample the tensor values from the source to the destination dimensions according to the axes and scaling factors. 
 <pre class="idl highlight def"><c- b>enum</c-> <dfn class="dfn-paneled idl-code" data-dfn-type="enum" data-export id="enumdef-mlinterpolationmode"><code><c- g>MLInterpolationMode</c-></code></dfn> {
   <dfn class="dfn-paneled idl-code" data-dfn-for="MLInterpolationMode" data-dfn-type="enum-value" data-export id="dom-mlinterpolationmode-nearest-neighbor"><code><c- s>"nearest-neighbor"</c-></code></dfn>,
   <dfn class="dfn-paneled idl-code" data-dfn-for="MLInterpolationMode" data-dfn-type="enum-value" data-export id="dom-mlinterpolationmode-linear"><code><c- s>"linear"</c-></code></dfn>
@@ -7284,20 +7284,20 @@ <h4 class="heading settled" data-level="7.7.36" 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-scales"><code>scales</code></dfn>, <span> of type sequence&lt;<a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-float" id="ref-for-idl-float①">float</a>></span>
     <dd data-md>
      <p>A list of length 2.
-Specifies the scaling factor in each spatial dimensions of the input: <em>[scaleHeight, scaleWidth]</em>.
+Specifies the scaling factor for each input dimension from <code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes①">axes</a></code> : <em>[scaleForFirstAxis, scaleForSecondAxis]</em>.
 The default value is [1.0, 1.0].</p>
     <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 spatial dimensions of the input: <em>[sizeHeight, sizeWidth]</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 each spatial dimension 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, ForSecondAxis]</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>
     <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.
-Specifies the two consecutive dimensions of the input tensor to which the interpolation algorithm applies. The valid values are [0, 1], [1, 2] or [2, 3].
+Specifies the two dimensions of the input tensor to which the interpolation algorithm applies.
 The default value is [2, 3].</p>
    </dl>
    <details class="algorithm" data-algorithm="check resample options" data-algorithm-for="MLGraphBuilder" open>
-    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-check-resample-options">check resample options</dfn> given <var>options</var>, run the following steps: </summary>
+    <summary> To <dfn class="dfn-paneled" data-dfn-for="MLGraphBuilder" data-dfn-type="dfn" data-noexport id="mlgraphbuilder-check-resample-options">check resample options</dfn> given <var>options</var> and <var>input</var>, run the following steps: </summary>
     <ol>
      <li data-md>
       <p>If <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-scales" id="ref-for-dom-mlresample2doptions-scales②">scales</a></code> does not <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨④">exist</a>, set it to the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④②">list</a> « 1.0, 1.0 ».</p>
@@ -7306,9 +7306,9 @@ <h4 class="heading settled" data-level="7.7.36" id="api-mlgraphbuilder-resample2
      <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-exists⑨⑤">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-axes①">axes</a></code> does not <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#map-exists" id="ref-for-map-exists⑨⑥">exists</a>, set it to the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④③">list</a> « 2, 3 ».</p>
+      <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-exists⑨⑥">exists</a>, set it to the <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④③">list</a> « 2, 3 ».</p>
      <li data-md>
-      <p>Otherwise, if its value is not one of « 0, 1», « 1, 2», « 2, 3 », return false.</p>
+      <p>Otherwise, if <var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes④">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-range①⓪">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑥">rank</a>, exclusive, then return false.</p>
      <li data-md>
       <p>Return true.</p>
     </ol>
@@ -7321,16 +7321,16 @@ <h4 class="heading settled" data-level="7.7.36" id="api-mlgraphbuilder-resample2
      <li data-md>
       <p>Let <var>outputShape</var> be a <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-clone" id="ref-for-list-clone①⑦">clone</a> of <var>inputDescriptor</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperanddescriptor-dimensions" id="ref-for-dom-mloperanddescriptor-dimensions①③">dimensions</a></code>.</p>
      <li data-md>
-      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①②">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①⓪">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-axes②">axes</a></code>'s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑥">size</a>, exclusive:</p>
+      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①②">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-size③⑥">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-exists⑨⑦">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>
        <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-axes③">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>
+        <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>
         <p>If <var>size</var> is not a <a data-link-type="dfn" href="#valid-dimension" id="ref-for-valid-dimension①④">valid dimension</a>, then return failure.</p>
        <li data-md>
-        <p>Set <var>outputShape</var>[<var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes④">axes</a></code>[<var>index</var>]] to <var>size</var>.</p>
+        <p>Set <var>outputShape</var>[<var>options</var>.<code class="idl"><a data-link-type="idl" href="#dom-mlresample2doptions-axes" id="ref-for-dom-mlresample2doptions-axes⑦">axes</a></code>[<var>index</var>]] to <var>size</var>.</p>
       </ol>
      <li data-md>
       <p>Return the result of <a data-link-type="dfn" href="#create-an-mloperanddescriptor" id="ref-for-create-an-mloperanddescriptor①⑧">creating an MLOperandDescriptor</a> given <var>inputDescriptor</var>.<code class="idl"><a data-link-type="idl" href="#dom-mloperanddescriptor-datatype" id="ref-for-dom-mloperanddescriptor-datatype⑥">dataType</a></code> and <var>outputShape</var>.</p>
@@ -7346,9 +7346,9 @@ <h4 class="heading settled" data-level="7.7.36" id="api-mlgraphbuilder-resample2
      <li data-md>
       <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①③①">dataType</a> is not <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④⑤">"float32"</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④③">"float16"</a></code>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③②⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②①">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑥">rank</a> is not 4, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②②">TypeError</a></code>.</p>
+      <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑦">rank</a> is not 4, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②②">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <a data-link-type="dfn" href="#mlgraphbuilder-check-resample-options" id="ref-for-mlgraphbuilder-check-resample-options">checking resample options</a> given <var>options</var> returns false, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③①">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②③">TypeError</a></code>.</p>
+      <p>If <a data-link-type="dfn" href="#mlgraphbuilder-check-resample-options" id="ref-for-mlgraphbuilder-check-resample-options">checking resample options</a> given <var>options</var> and <var>input</var> returns false, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③①">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②③">TypeError</a></code>.</p>
      <li data-md>
       <p>Let <var>desc</var> be the result of <a data-link-type="dfn" href="#mlgraphbuilder-calculate-resample-output-sizes" id="ref-for-mlgraphbuilder-calculate-resample-output-sizes">calculating resample output sizes</a> given <var>input</var> and <var>options</var>. If that returns failure, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③③②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②②④">TypeError</a></code>.</p>
      <li data-md>
@@ -7506,9 +7506,9 @@ <h4 class="heading settled" data-level="7.7.39" 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-mloperand③⑥⑦">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-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-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-rank④⑦">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-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-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-rank④⑧">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>
      <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-sequence④④">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-rank④⑧">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 data-link-type="dfn" href="https://webidl.spec.whatwg.org/#idl-sequence" id="ref-for-idl-sequence④④">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-rank④⑨">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>
      <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>
@@ -7524,9 +7524,9 @@ <h4 class="heading settled" data-level="7.7.39" id="api-mlgraphbuilder-slice"><s
      <li data-md>
       <p>If any of <var>sizes</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-item" id="ref-for-list-item⑥">items</a> are 0, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③①">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>starts</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑧">size</a> and <var>sizes</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑨">size</a> are not both equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank④⑨">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③②">TypeError</a></code>.</p>
+      <p>If <var>starts</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑧">size</a> and <var>sizes</var>’s <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size③⑨">size</a> are not both equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⓪">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③②">TypeError</a></code>.</p>
      <li data-md>
-      <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>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⓪">rank</a>, exclusive:</p>
+      <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-range①②">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤①">rank</a>, exclusive:</p>
       <ol>
        <li data-md>
         <p>If <var>sizes</var>[<var>index</var>] is 0, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④④">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③③">TypeError</a></code>.</p>
@@ -7589,7 +7589,7 @@ <h4 class="heading settled" data-level="7.7.40" id="api-mlgraphbuilder-softmax-m
      <li data-md>
       <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-datatype" id="ref-for-mloperand-datatype①③③">dataType</a> is not <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float32" id="ref-for-dom-mloperanddatatype-float32④⑦">"float32"</a></code> or <code class="idl"><a data-link-type="idl" href="#dom-mloperanddatatype-float16" id="ref-for-dom-mloperanddatatype-float16④⑤">"float16"</a></code>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③④⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③⑦">TypeError</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-rank⑤①">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③⑧">TypeError</a></code>.</p>
+      <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-rank⑤②">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤⓪">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②③⑧">TypeError</a></code>.</p>
      <li data-md>
       <p><em>Make graph connections:</em></p>
       <ol>
@@ -7769,7 +7769,7 @@ <h4 class="heading settled" data-level="7.7.43" id="api-mlgraphbuilder-split"><s
    <dl>
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLSplitOptions" data-dfn-type="dict-member" data-export id="dom-mlsplitoptions-axis"><code>axis</code></dfn>, <span> of type <a data-link-type="idl-name" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑦⓪">unsigned long</a>, defaulting to <code>0</code></span>
     <dd data-md>
-     <p>The dimension along which to split. Its value must be in the range [0, N-1] where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤②">rank</a> of the input tensor.</p>
+     <p>The dimension along which to split. Its value must be in the range [0, N-1] where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤③">rank</a> of the input tensor.</p>
    </dl>
    <details class="algorithm" data-algorithm="split(input, splits, options)" data-algorithm-for="MLGraphBuilder" open>
     <summary> The <dfn class="dfn-paneled idl-code" data-dfn-for="MLGraphBuilder" data-dfn-type="method" data-export data-lt="split(input, splits, options)|split(input, splits)" id="dom-mlgraphbuilder-split"><code>split(<var>input</var>, <var>splits</var>, <var>options</var>)</code></dfn> method steps are: </summary>
@@ -7781,7 +7781,7 @@ <h4 class="heading settled" data-level="7.7.43" id="api-mlgraphbuilder-split"><s
      <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>
      <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-rank⑤③">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②④④">TypeError</a></code>.</p>
+      <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-rank⑤④">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑤⑨">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②④④">TypeError</a></code>.</p>
      <li data-md>
       <p>If <var>splits</var> is an <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#idl-unsigned-long" id="ref-for-idl-unsigned-long⑦①">unsigned long</a></code>:</p>
       <ol>
@@ -7809,7 +7809,7 @@ <h4 class="heading settled" data-level="7.7.43" id="api-mlgraphbuilder-split"><s
        <li data-md>
         <p>Let <var>outputs</var> be a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④⑤">list</a>.</p>
        <li data-md>
-        <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①④">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①②">the range</a> 0 to <var>splitCount</var>, exclusive:</p>
+        <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①④">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①③">the range</a> 0 to <var>splitCount</var>, exclusive:</p>
         <ol>
          <li data-md>
           <p>Let <var>operand</var> be the result of <a data-link-type="dfn" href="#copy-an-mloperand" id="ref-for-copy-an-mloperand①⑦">copying an MLOperand</a> given <var>input</var>.</p>
@@ -7932,8 +7932,8 @@ <h4 class="heading settled" data-level="7.7.45" id="api-mlgraphbuilder-transpose
     <dt data-md><dfn class="dfn-paneled idl-code" data-dfn-for="MLTransposeOptions" data-dfn-type="dict-member" data-export id="dom-mltransposeoptions-permutation"><code>permutation</code></dfn>, <span> of type <code class="idl-code">sequence&lt;[EnforceRange] unsigned long></code></span>
     <dd data-md>
      <p>The values used to permute the output shape.
-The default is [N-1, ..., 0], where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤④">rank</a> of the input tensor, e.g. [2,1,0] for a 3-D tensor.
-These default values cause the output to become a transposed tensor of the input. When specified, the number of values must be the same as the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑤">rank</a> of the input tensor, and the values must be within the range from 0 to N-1 with no duplicates.</p>
+The default is [N-1, ..., 0], where N is the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑤">rank</a> of the input tensor, e.g. [2,1,0] for a 3-D tensor.
+These default values cause the output to become a transposed tensor of the input. When specified, the number of values must be the same as the <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑥">rank</a> of the input tensor, and the values must be within the range from 0 to N-1 with no duplicates.</p>
    </dl>
    <div>
      <strong>Arguments:</strong> 
@@ -7958,9 +7958,9 @@ <h4 class="heading settled" data-level="7.7.45" id="api-mlgraphbuilder-transpose
       <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-exists⑨⑨">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-size④④">size</a> is not equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑥">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥⑧">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤①">TypeError</a></code>.</p>
+        <p>If its <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-size" id="ref-for-list-size④④">size</a> is not equal to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑦">rank</a>, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥⑧">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤①">TypeError</a></code>.</p>
        <li data-md>
-        <p>If its values are not in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①③">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑦">rank</a> exclusive, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥⑨">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>
+        <p>If its values are not in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①④">the range</a> 0 to <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑧">rank</a> exclusive, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑥⑨">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 it contains duplicate values, 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-typeerror②⑤③">TypeError</a></code>.</p>
       </ol>
@@ -8020,7 +8020,7 @@ <h4 class="heading settled" data-level="7.7.46" id="api-mlgraphbuilder-triangula
      <li data-md>
       <p>If <a data-link-type="dfn" href="#mlgraphbuilder-validate-operand" id="ref-for-mlgraphbuilder-validate-operand④③">validating operand</a> with <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#this" id="ref-for-this①③⑨">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-throw③⑦②">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤④">TypeError</a></code>.</p>
      <li data-md>
-      <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑧">rank</a> is less than 2, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤⑤">TypeError</a></code>.</p>
+      <p>If <var>input</var>’s <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑨">rank</a> is less than 2, then <a data-link-type="dfn" href="https://webidl.spec.whatwg.org/#dfn-throw" id="ref-for-dfn-throw③⑦③">throw</a> a <code class="idl"><a data-link-type="idl" href="https://webidl.spec.whatwg.org/#exceptiondef-typeerror" id="ref-for-exceptiondef-typeerror②⑤⑤">TypeError</a></code>.</p>
      <li data-md>
       <p><em>Make graph connections:</em></p>
       <ol>
@@ -8099,7 +8099,7 @@ <h4 class="heading settled" data-level="7.7.46" id="api-mlgraphbuilder-triangula
    </div>
    <h4 class="heading settled" data-level="7.7.47" id="api-mlgraphbuilder-where"><span class="secno">7.7.47. </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. 
-   <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-broadcastable⑤">bidirectionally broadcastable</a>. The <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑤⑨">rank</a> of the output tensor is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑥⓪">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>
+   <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-broadcastable⑤">bidirectionally broadcastable</a>. The <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑥⓪">rank</a> of the output tensor is the maximum <a data-link-type="dfn" href="#mloperand-rank" id="ref-for-mloperand-rank⑥①">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-mlgraphbuilder⑥④"><c- g>MLGraphBuilder</c-></a> {
   <a data-link-type="idl-name" href="#mloperand" id="ref-for-mloperand③⑨⑦"><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-mloperand③⑨⑧"><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-mloperand③⑨⑨"><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>,
@@ -8200,7 +8200,7 @@ <h3 class="heading settled" data-level="8.1" id="algorithms-broadcasting"><span
      <li data-md>
       <p>Let <var>outputShape</var> be a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list④⑧">list</a>.</p>
      <li data-md>
-      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①⑤">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①④">the range</a> 0 to <var>sizeTo</var>, exclusive:</p>
+      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①⑤">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①⑤">the range</a> 0 to <var>sizeTo</var>, exclusive:</p>
       <ol>
        <li data-md>
         <p>Let <var>dimFrom</var> be <var>paddedShapeFrom</var>[<var>index</var>].</p>
@@ -8236,7 +8236,7 @@ <h3 class="heading settled" data-level="8.1" id="algorithms-broadcasting"><span
      <li data-md>
       <p>Let <var>outputShape</var> be a new <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list" id="ref-for-list⑤①">list</a>.</p>
      <li data-md>
-      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①⑥">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①⑤">the range</a> 0 to <var>outputSize</var>, exclusive:</p>
+      <p><a data-link-type="dfn" href="https://infra.spec.whatwg.org/#list-iterate" id="ref-for-list-iterate①⑥">For each</a> <var>index</var> in <a data-link-type="dfn" href="https://infra.spec.whatwg.org/#the-range" id="ref-for-the-range①⑥">the range</a> 0 to <var>outputSize</var>, exclusive:</p>
       <ol>
        <li data-md>
         <p>Let <var>dimA</var> be <var>paddedA</var>[<var>index</var>].</p>
@@ -10671,7 +10671,7 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
 "dom-mlrecurrentnetworkdirection-forward": {"dfnID":"dom-mlrecurrentnetworkdirection-forward","dfnText":"\"forward\"","external":false,"refSections":[],"url":"#dom-mlrecurrentnetworkdirection-forward"},
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-"dom-mlresample2doptions-axes": {"dfnID":"dom-mlresample2doptions-axes","dfnText":"axes","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlresample2doptions-axes"},{"id":"ref-for-dom-mlresample2doptions-axes\u2460"},{"id":"ref-for-dom-mlresample2doptions-axes\u2461"},{"id":"ref-for-dom-mlresample2doptions-axes\u2462"},{"id":"ref-for-dom-mlresample2doptions-axes\u2463"}],"title":"7.7.36. resample2d"}],"url":"#dom-mlresample2doptions-axes"},
+"dom-mlresample2doptions-axes": {"dfnID":"dom-mlresample2doptions-axes","dfnText":"axes","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlresample2doptions-axes"},{"id":"ref-for-dom-mlresample2doptions-axes\u2460"},{"id":"ref-for-dom-mlresample2doptions-axes\u2461"},{"id":"ref-for-dom-mlresample2doptions-axes\u2462"},{"id":"ref-for-dom-mlresample2doptions-axes\u2463"},{"id":"ref-for-dom-mlresample2doptions-axes\u2464"},{"id":"ref-for-dom-mlresample2doptions-axes\u2465"},{"id":"ref-for-dom-mlresample2doptions-axes\u2466"}],"title":"7.7.36. resample2d"}],"url":"#dom-mlresample2doptions-axes"},
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 "dom-mlresample2doptions-scales": {"dfnID":"dom-mlresample2doptions-scales","dfnText":"scales","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlresample2doptions-scales"},{"id":"ref-for-dom-mlresample2doptions-scales\u2460"},{"id":"ref-for-dom-mlresample2doptions-scales\u2461"},{"id":"ref-for-dom-mlresample2doptions-scales\u2462"}],"title":"7.7.36. resample2d"}],"url":"#dom-mlresample2doptions-scales"},
 "dom-mlresample2doptions-sizes": {"dfnID":"dom-mlresample2doptions-sizes","dfnText":"sizes","external":false,"refSections":[{"refs":[{"id":"ref-for-dom-mlresample2doptions-sizes"},{"id":"ref-for-dom-mlresample2doptions-sizes\u2460"},{"id":"ref-for-dom-mlresample2doptions-sizes\u2461"},{"id":"ref-for-dom-mlresample2doptions-sizes\u2462"}],"title":"7.7.36. resample2d"}],"url":"#dom-mlresample2doptions-sizes"},
@@ -10706,7 +10706,7 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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 "mlcontext": {"dfnID":"mlcontext","dfnText":"MLContext","external":false,"refSections":[{"refs":[{"id":"ref-for-mlcontext"},{"id":"ref-for-mlcontext\u2460"},{"id":"ref-for-mlcontext\u2461"}],"title":"3. Security Considerations"},{"refs":[{"id":"ref-for-mlcontext\u2462"}],"title":"6.1. Overview"},{"refs":[{"id":"ref-for-mlcontext\u2463"},{"id":"ref-for-mlcontext\u2464"},{"id":"ref-for-mlcontext\u2465"}],"title":"6.2. Device Selection"},{"refs":[{"id":"ref-for-mlcontext\u2466"}],"title":"6.3. Task Source"},{"refs":[{"id":"ref-for-mlcontext\u2467"},{"id":"ref-for-mlcontext\u2468"}],"title":"7.2. ML interface"},{"refs":[{"id":"ref-for-mlcontext\u2460\u24ea"},{"id":"ref-for-mlcontext\u2460\u2460"}],"title":"7.2.2. createContext()"},{"refs":[{"id":"ref-for-mlcontext\u2460\u2461"},{"id":"ref-for-mlcontext\u2460\u2462"},{"id":"ref-for-mlcontext\u2460\u2463"},{"id":"ref-for-mlcontext\u2460\u2464"},{"id":"ref-for-mlcontext\u2460\u2465"},{"id":"ref-for-mlcontext\u2460\u2466"},{"id":"ref-for-mlcontext\u2460\u2467"}],"title":"7.3. MLContext interface"},{"refs":[{"id":"ref-for-mlcontext\u2460\u2468"}],"title":"7.3.2. compute()"},{"refs":[{"id":"ref-for-mlcontext\u2461\u24ea"},{"id":"ref-for-mlcontext\u2461\u2460"}],"title":"7.4. MLGraph interface"},{"refs":[{"id":"ref-for-mlcontext\u2461\u2461"},{"id":"ref-for-mlcontext\u2461\u2462"}],"title":"7.6. MLOperand interface"},{"refs":[{"id":"ref-for-mlcontext\u2461\u2463"},{"id":"ref-for-mlcontext\u2461\u2464"},{"id":"ref-for-mlcontext\u2461\u2465"},{"id":"ref-for-mlcontext\u2461\u2466"},{"id":"ref-for-mlcontext\u2461\u2467"}],"title":"7.7. MLGraphBuilder interface"},{"refs":[{"id":"ref-for-mlcontext\u2461\u2468"}],"title":"7.7.1. MLGraphBuilder constructor"}],"url":"#mlcontext"},
@@ -10733,7 +10733,7 @@ <h2 class="no-num no-ref heading settled" id="issues-index"><span class="content
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Element-wise binary operations"},{"refs":[{"id":"ref-for-mloperand\u2460\u2461\u2464"},{"id":"ref-for-mloperand\u2460\u2461\u2465"},{"id":"ref-for-mloperand\u2460\u2461\u2466"},{"id":"ref-for-mloperand\u2460\u2461\u2467"},{"id":"ref-for-mloperand\u2460\u2461\u2468"},{"id":"ref-for-mloperand\u2460\u2462\u24ea"},{"id":"ref-for-mloperand\u2460\u2462\u2460"},{"id":"ref-for-mloperand\u2460\u2462\u2461"},{"id":"ref-for-mloperand\u2460\u2462\u2462"},{"id":"ref-for-mloperand\u2460\u2462\u2463"},{"id":"ref-for-mloperand\u2460\u2462\u2464"},{"id":"ref-for-mloperand\u2460\u2462\u2465"},{"id":"ref-for-mloperand\u2460\u2462\u2466"},{"id":"ref-for-mloperand\u2460\u2462\u2467"},{"id":"ref-for-mloperand\u2460\u2462\u2468"},{"id":"ref-for-mloperand\u2460\u2463\u24ea"},{"id":"ref-for-mloperand\u2460\u2463\u2460"},{"id":"ref-for-mloperand\u2460\u2463\u2461"},{"id":"ref-for-mloperand\u2460\u2463\u2462"},{"id":"ref-for-mloperand\u2460\u2463\u2463"},{"id":"ref-for-mloperand\u2460\u2463\u2464"},{"id":"ref-for-mloperand\u2460\u2463\u2465"}],"title":"7.7.13. Element-wise logical operations"},{"refs":[{"id":"ref-for-mloperand\u2460\u2463\u2466"},{"id":"ref-for-mloperand\u2460\u2463\u2467"},{"id":"ref-for-mloperand\u2460\u2463\u2468"},{"id":"ref-for-mloperand\u2460\u2464\u24ea"},{"id":"ref-for-mloperand\u2460\u2464\u2460"},{"id":"ref-for-mloperand\u2460\u2464\u2461"},{"id":"ref-for-mloperand\u2460\u2464\u2462"},{"id":"ref-for-mloperand\u2460\u2464\u2463"},{"id":"ref-for-mloperand\u2460\u2464\u2464"},{"id":"ref-for-mloperand\u2460\u2464\u2465"},{"id":"ref-for-mloperand\u2460\u2464\u2466"},{"id":"ref-for-mloperand\u2460\u2464\u2467"},{"id":"ref-for-mloperand\u2460\u2464\u2468"},{"id":"ref-for-mloperand\u2460\u2465\u24ea"},{"id":"ref-for-mloperand\u2460\u2465\u2460"},{"id":"ref-for-mloperand\u2460\u2465\u2461"},{"id":"ref-for-mloperand\u2460\u2465\u2462"},{"id":"ref-for-mloperand\u2460\u2465\u2463"},{"id":"ref-for-mloperand\u2460\u2465\u2464"},{"id":"ref-for-mloperand\u2460\u2465\u2465"},{"id":"ref-for-mloperand\u2460\u2465\u2466"},{"id":"ref-for-mloperand\u2460\u2465\u2467"},{"id":"ref-for-mloperand\u2460\u2465\u2468"},{"id":"ref-for-mloperand\u2460\u2466\u24ea"},{"id":"ref-for-mloperand\u2460\u2466\u2460"},{"id":"ref-for-mloperand\u2460\u2466\u2461"},{"id":"ref-for-mloperand\u2460\u2466\u2462"},{"id":"ref-for-mloperand\u2460\u2466\u2463"},{"id":"ref-for-mloperand\u2460\u2466\u2464"}],"title":"7.7.14. Element-wise unary operations"},{"refs":[{"id":"ref-for-mloperand\u2460\u2466\u2465"},{"id":"ref-for-mloperand\u2460\u2466\u2466"},{"id":"ref-for-mloperand\u2460\u2466\u2467"},{"id":"ref-for-mloperand\u2460\u2466\u2468"}],"title":"7.7.15. elu"},{"refs":[{"id":"ref-for-mloperand\u2460\u2467\u24ea"},{"id":"ref-for-mloperand\u2460\u2467\u2460"},{"id":"ref-for-mloperand\u2460\u2467\u2461"},{"id":"ref-for-mloperand\u2460\u2467\u2462"}],"title":"7.7.16. expand"},{"refs":[{"id":"ref-for-mloperand\u2460\u2467\u2463"},{"id":"ref-for-mloperand\u2460\u2467\u2464"},{"id":"ref-for-mloperand\u2460\u2467\u2465"},{"id":"ref-for-mloperand\u2460\u2467\u2466"},{"id":"ref-for-mloperand\u2460\u2467\u2467"},{"id":"ref-for-mloperand\u2460\u2467\u2468"}],"title":"7.7.17. gather"},{"refs":[{"id":"ref-for-mloperand\u2460\u2468\u24ea"},{"id":"ref-for-mloperand\u2460\u2468\u2460"},{"id":"ref-for-mloperand\u2460\u2468\u2461"},{"id":"ref-for-mloperand\u2460\u2468\u2462"}],"title":"7.7.18. gelu"},{"refs":[{"id":"ref-for-mloperand\u2460\u2468\u2463"},{"id":"ref-for-mloperand\u2460\u2468\u2464"},{"id":"ref-for-mloperand\u2460\u2468\u2465"},{"id":"ref-for-mloperand\u2460\u2468\u2466"},{"id":"ref-for-mloperand\u2460\u2468\u2467"},{"id":"ref-for-mloperand\u2460\u2468\u2468"},{"id":"ref-for-mloperand\u2461\u24ea\u24ea"},{"id":"ref-for-mloperand\u2461\u24ea\u2460"}],"title":"7.7.19. gemm"},{"refs":[{"id":"ref-for-mloperand\u2461\u24ea\u2461"},{"id":"ref-for-mloperand\u2461\u24ea\u2462"},{"id":"ref-for-mloperand\u2461\u24ea\u2463"},{"id":"ref-for-mloperand\u2461\u24ea\u2464"},{"id":"ref-for-mloperand\u2461\u24ea\u2465"},{"id":"ref-for-mloperand\u2461\u24ea\u2466"},{"id":"ref-for-mloperand\u2461\u24ea\u2467"},{"id":"ref-for-mloperand\u2461\u24ea\u2468"},{"id":"ref-for-mloperand\u2461\u2460\u24ea"},{"id":"ref-for-mloperand\u2461\u2460\u2460"},{"id":"ref-for-mloperand\u2461\u2460\u2461"},{"id":"ref-for-mloperand\u2461\u2460\u2462"},{"id":"ref-for-mloperand\u2461\u2460\u2463"},{"id":"ref-for-mloperand\u2461\u2460\u2464"}],"title":"7.7.20. gru"},{"refs":[{"id":"ref-for-mloperand\u2461\u2460\u2465"},{"id":"ref-for-mloperand\u2461\u2460\u2466"},{"id":"ref-for-mloperand\u2461\u2460\u2467"},{"id":"ref-for-mloperand\u2461\u2460\u2468"},{"id":"ref-for-mloperand\u2461\u2461\u24ea"},{"id":"ref-for-mloperand\u2461\u2461\u2460"},{"id":"ref-for-mloperand\u2461\u2461\u2461"},{"id":"ref-for-mloperand\u2461\u2461\u2462"},{"id":"ref-for-mloperand\u2461\u2461\u2463"},{"id":"ref-for-mloperand\u2461\u2461\u2464"},{"id":"ref-for-mloperand\u2461\u2461\u2465"},{"id":"ref-for-mloperand\u2461\u2461\u2466"},{"id":"ref-for-mloperand\u2461\u2461\u2467"},{"id":"ref-for-mloperand\u2461\u2461\u2468"}],"title":"7.7.21. gruCell"},{"refs":[{"id":"ref-for-mloperand\u2461\u2462\u24ea"},{"id":"ref-for-mloperand\u2461\u2462\u2460"},{"id":"ref-for-mloperand\u2461\u2462\u2461"},{"id":"ref-for-mloperand\u2461\u2462\u2462"}],"title":"7.7.22. hardSigmoid"},{"refs":[{"id":"ref-for-mloperand\u2461\u2462\u2463"},{"id":"ref-for-mloperand\u2461\u2462\u2464"},{"id":"ref-for-mloperand\u2461\u2462\u2465"},{"id":"ref-for-mloperand\u2461\u2462\u2466"}],"title":"7.7.23. hardSwish"},{"refs":[{"id":"ref-for-mloperand\u2461\u2462\u2467"},{"id":"ref-for-mloperand\u2461\u2462\u2468"},{"id":"ref-for-mloperand\u2461\u2463\u24ea"},{"id":"ref-for-mloperand\u2461\u2463\u2460"},{"id":"ref-for-mloperand\u2461\u2463\u2461"},{"id":"ref-for-mloperand\u2461\u2463\u2462"},{"id":"ref-for-mloperand\u2461\u2463\u2463"},{"id":"ref-for-mloperand\u2461\u2463\u2464"}],"title":"7.7.24. instanceNormalization"},{"refs":[{"id":"ref-for-mloperand\u2461\u2463\u2465"},{"id":"ref-for-mloperand\u2461\u2463\u2466"},{"id":"ref-for-mloperand\u2461\u2463\u2467"},{"id":"ref-for-mloperand\u2461\u2463\u2468"},{"id":"ref-for-mloperand\u2461\u2464\u24ea"},{"id":"ref-for-mloperand\u2461\u2464\u2460"},{"id":"ref-for-mloperand\u2461\u2464\u2461"},{"id":"ref-for-mloperand\u2461\u2464\u2462"}],"title":"7.7.25. layerNormalization"},{"refs":[{"id":"ref-for-mloperand\u2461\u2464\u2463"},{"id":"ref-for-mloperand\u2461\u2464\u2464"},{"id":"ref-for-mloperand\u2461\u2464\u2465"},{"id":"ref-for-mloperand\u2461\u2464\u2466"}],"title":"7.7.26. leakyRelu"},{"refs":[{"id":"ref-for-mloperand\u2461\u2464\u2467"},{"id":"ref-for-mloperand\u2461\u2464\u2468"},{"id":"ref-for-mloperand\u2461\u2465\u24ea"},{"id":"ref-for-mloperand\u2461\u2465\u2460"}],"title":"7.7.27. linear"},{"refs":[{"id":"ref-for-mloperand\u2461\u2465\u2461"},{"id":"ref-for-mloperand\u2461\u2465\u2462"},{"id":"ref-for-mloperand\u2461\u2465\u2463"},{"id":"ref-for-mloperand\u2461\u2465\u2464"},{"id":"ref-for-mloperand\u2461\u2465\u2465"},{"id":"ref-for-mloperand\u2461\u2465\u2466"},{"id":"ref-for-mloperand\u2461\u2465\u2467"},{"id":"ref-for-mloperand\u2461\u2465\u2468"},{"id":"ref-for-mloperand\u2461\u2466\u24ea"},{"id":"ref-for-mloperand\u2461\u2466\u2460"},{"id":"ref-for-mloperand\u2461\u2466\u2461"},{"id":"ref-for-mloperand\u2461\u2466\u2462"},{"id":"ref-for-mloperand\u2461\u2466\u2463"},{"id":"ref-for-mloperand\u2461\u2466\u2464"},{"id":"ref-for-mloperand\u2461\u2466\u2465"},{"id":"ref-for-mloperand\u2461\u2466\u2466"},{"id":"ref-for-mloperand\u2461\u2466\u2467"},{"id":"ref-for-mloperand\u2461\u2466\u2468"}],"title":"7.7.28. lstm"},{"refs":[{"id":"ref-for-mloperand\u2461\u2467\u24ea"},{"id":"ref-for-mloperand\u2461\u2467\u2460"},{"id":"ref-for-mloperand\u2461\u2467\u2461"},{"id":"ref-for-mloperand\u2461\u2467\u2462"},{"id":"ref-for-mloperand\u2461\u2467\u2463"},{"id":"ref-for-mloperand\u2461\u2467\u2464"},{"id":"ref-for-mloperand\u2461\u2467\u2465"},{"id":"ref-for-mloperand\u2461\u2467\u2466"},{"id":"ref-for-mloperand\u2461\u2467\u2467"},{"id":"ref-for-mloperand\u2461\u2467\u2468"},{"id":"ref-for-mloperand\u2461\u2468\u24ea"},{"id":"ref-for-mloperand\u2461\u2468\u2460"},{"id":"ref-for-mloperand\u2461\u2468\u2461"},{"id":"ref-for-mloperand\u2461\u2468\u2462"},{"id":"ref-for-mloperand\u2461\u2468\u2463"},{"id":"ref-for-mloperand\u2461\u2468\u2464"},{"id":"ref-for-mloperand\u2461\u2468\u2465"},{"id":"ref-for-mloperand\u2461\u2468\u2466"}],"title":"7.7.29. lstmCell"},{"refs":[{"id":"ref-for-mloperand\u2461\u2468\u2467"},{"id":"ref-for-mloperand\u2461\u2468\u2468"},{"id":"ref-for-mloperand\u2462\u24ea\u24ea"},{"id":"ref-for-mloperand\u2462\u24ea\u2460"},{"id":"ref-for-mloperand\u2462\u24ea\u2461"},{"id":"ref-for-mloperand\u2462\u24ea\u2462"},{"id":"ref-for-mloperand\u2462\u24ea\u2463"},{"id":"ref-for-mloperand\u2462\u24ea\u2464"}],"title":"7.7.30. matmul"},{"refs":[{"id":"ref-for-mloperand\u2462\u24ea\u2465"},{"id":"ref-for-mloperand\u2462\u24ea\u2466"},{"id":"ref-for-mloperand\u2462\u24ea\u2467"},{"id":"ref-for-mloperand\u2462\u24ea\u2468"}],"title":"7.7.31. pad"},{"refs":[{"id":"ref-for-mloperand\u2462\u2460\u24ea"},{"id":"ref-for-mloperand\u2462\u2460\u2460"},{"id":"ref-for-mloperand\u2462\u2460\u2461"},{"id":"ref-for-mloperand\u2462\u2460\u2462"},{"id":"ref-for-mloperand\u2462\u2460\u2463"},{"id":"ref-for-mloperand\u2462\u2460\u2464"},{"id":"ref-for-mloperand\u2462\u2460\u2465"},{"id":"ref-for-mloperand\u2462\u2460\u2466"},{"id":"ref-for-mloperand\u2462\u2460\u2467"}],"title":"7.7.32. Pooling operations"},{"refs":[{"id":"ref-for-mloperand\u2462\u2460\u2468"},{"id":"ref-for-mloperand\u2462\u2461\u24ea"},{"id":"ref-for-mloperand\u2462\u2461\u2460"},{"id":"ref-for-mloperand\u2462\u2461\u2461"},{"id":"ref-for-mloperand\u2462\u2461\u2462"},{"id":"ref-for-mloperand\u2462\u2461\u2463"}],"title":"7.7.33. prelu"},{"refs":[{"id":"ref-for-mloperand\u2462\u2461\u2464"},{"id":"ref-for-mloperand\u2462\u2461\u2465"},{"id":"ref-for-mloperand\u2462\u2461\u2466"},{"id":"ref-for-mloperand\u2462\u2461\u2467"},{"id":"ref-for-mloperand\u2462\u2461\u2468"},{"id":"ref-for-mloperand\u2462\u2462\u24ea"},{"id":"ref-for-mloperand\u2462\u2462\u2460"},{"id":"ref-for-mloperand\u2462\u2462\u2461"},{"id":"ref-for-mloperand\u2462\u2462\u2462"},{"id":"ref-for-mloperand\u2462\u2462\u2463"},{"id":"ref-for-mloperand\u2462\u2462\u2464"},{"id":"ref-for-mloperand\u2462\u2462\u2465"},{"id":"ref-for-mloperand\u2462\u2462\u2466"},{"id":"ref-for-mloperand\u2462\u2462\u2467"},{"id":"ref-for-mloperand\u2462\u2462\u2468"},{"id":"ref-for-mloperand\u2462\u2463\u24ea"},{"id":"ref-for-mloperand\u2462\u2463\u2460"},{"id":"ref-for-mloperand\u2462\u2463\u2461"},{"id":"ref-for-mloperand\u2462\u2463\u2462"},{"id":"ref-for-mloperand\u2462\u2463\u2463"},{"id":"ref-for-mloperand\u2462\u2463\u2464"},{"id":"ref-for-mloperand\u2462\u2463\u2465"},{"id":"ref-for-mloperand\u2462\u2463\u2466"}],"title":"7.7.34. Reduction operations"},{"refs":[{"id":"ref-for-mloperand\u2462\u2463\u2467"},{"id":"ref-for-mloperand\u2462\u2463\u2468"},{"id":"ref-for-mloperand\u2462\u2464\u24ea"},{"id":"ref-for-mloperand\u2462\u2464\u2460"}],"title":"7.7.35. relu"},{"refs":[{"id":"ref-for-mloperand\u2462\u2464\u2461"},{"id":"ref-for-mloperand\u2462\u2464\u2462"},{"id":"ref-for-mloperand\u2462\u2464\u2463"},{"id":"ref-for-mloperand\u2462\u2464\u2464"},{"id":"ref-for-mloperand\u2462\u2464\u2465"}],"title":"7.7.36. resample2d"},{"refs":[{"id":"ref-for-mloperand\u2462\u2464\u2466"},{"id":"ref-for-mloperand\u2462\u2464\u2467"},{"id":"ref-for-mloperand\u2462\u2464\u2468"},{"id":"ref-for-mloperand\u2462\u2465\u24ea"}],"title":"7.7.37. reshape"},{"refs":[{"id":"ref-for-mloperand\u2462\u2465\u2460"},{"id":"ref-for-mloperand\u2462\u2465\u2461"},{"id":"ref-for-mloperand\u2462\u2465\u2462"},{"id":"ref-for-mloperand\u2462\u2465\u2463"}],"title":"7.7.38. sigmoid"},{"refs":[{"id":"ref-for-mloperand\u2462\u2465\u2464"},{"id":"ref-for-mloperand\u2462\u2465\u2465"},{"id":"ref-for-mloperand\u2462\u2465\u2466"},{"id":"ref-for-mloperand\u2462\u2465\u2467"}],"title":"7.7.39. slice"},{"refs":[{"id":"ref-for-mloperand\u2462\u2465\u2468"},{"id":"ref-for-mloperand\u2462\u2466\u24ea"},{"id":"ref-for-mloperand\u2462\u2466\u2460"},{"id":"ref-for-mloperand\u2462\u2466\u2461"}],"title":"7.7.40. softmax"},{"refs":[{"id":"ref-for-mloperand\u2462\u2466\u2462"},{"id":"ref-for-mloperand\u2462\u2466\u2463"},{"id":"ref-for-mloperand\u2462\u2466\u2464"},{"id":"ref-for-mloperand\u2462\u2466\u2465"}],"title":"7.7.41. softplus"},{"refs":[{"id":"ref-for-mloperand\u2462\u2466\u2466"},{"id":"ref-for-mloperand\u2462\u2466\u2467"},{"id":"ref-for-mloperand\u2462\u2466\u2468"},{"id":"ref-for-mloperand\u2462\u2467\u24ea"}],"title":"7.7.42. softsign"},{"refs":[{"id":"ref-for-mloperand\u2462\u2467\u2460"},{"id":"ref-for-mloperand\u2462\u2467\u2461"},{"id":"ref-for-mloperand\u2462\u2467\u2462"},{"id":"ref-for-mloperand\u2462\u2467\u2463"}],"title":"7.7.43. split"},{"refs":[{"id":"ref-for-mloperand\u2462\u2467\u2464"},{"id":"ref-for-mloperand\u2462\u2467\u2465"},{"id":"ref-for-mloperand\u2462\u2467\u2466"},{"id":"ref-for-mloperand\u2462\u2467\u2467"}],"title":"7.7.44. tanh"},{"refs":[{"id":"ref-for-mloperand\u2462\u2467\u2468"},{"id":"ref-for-mloperand\u2462\u2468\u24ea"},{"id":"ref-for-mloperand\u2462\u2468\u2460"},{"id":"ref-for-mloperand\u2462\u2468\u2461"}],"title":"7.7.45. transpose"},{"refs":[{"id":"ref-for-mloperand\u2462\u2468\u2462"},{"id":"ref-for-mloperand\u2462\u2468\u2463"},{"id":"ref-for-mloperand\u2462\u2468\u2464"},{"id":"ref-for-mloperand\u2462\u2468\u2465"}],"title":"7.7.46. triangular"},{"refs":[{"id":"ref-for-mloperand\u2462\u2468\u2466"},{"id":"ref-for-mloperand\u2462\u2468\u2467"},{"id":"ref-for-mloperand\u2462\u2468\u2468"},{"id":"ref-for-mloperand\u2463\u24ea\u24ea"},{"id":"ref-for-mloperand\u2463\u24ea\u2460"},{"id":"ref-for-mloperand\u2463\u24ea\u2461"},{"id":"ref-for-mloperand\u2463\u24ea\u2462"},{"id":"ref-for-mloperand\u2463\u24ea\u2463"}],"title":"7.7.47. where"},{"refs":[{"id":"ref-for-mloperand\u2463\u24ea\u2464"}],"title":"8.2. Casting"}],"url":"#mloperand"},
 "mloperand-datatype": {"dfnID":"mloperand-datatype","dfnText":"dataType","external":false,"refSections":[{"refs":[{"id":"ref-for-mloperand-datatype"}],"title":"7.6.1.1. 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Element-wise logical operations"},{"refs":[{"id":"ref-for-mloperand-shape\u2461\u2467"}],"title":"7.7.16. expand"},{"refs":[{"id":"ref-for-mloperand-shape\u2461\u2468"},{"id":"ref-for-mloperand-shape\u2462\u24ea"}],"title":"7.7.17. gather"},{"refs":[{"id":"ref-for-mloperand-shape\u2462\u2460"},{"id":"ref-for-mloperand-shape\u2462\u2461"}],"title":"7.7.19. gemm"},{"refs":[{"id":"ref-for-mloperand-shape\u2462\u2462"},{"id":"ref-for-mloperand-shape\u2462\u2463"},{"id":"ref-for-mloperand-shape\u2462\u2464"},{"id":"ref-for-mloperand-shape\u2462\u2465"},{"id":"ref-for-mloperand-shape\u2462\u2466"},{"id":"ref-for-mloperand-shape\u2462\u2467"},{"id":"ref-for-mloperand-shape\u2462\u2468"},{"id":"ref-for-mloperand-shape\u2463\u24ea"}],"title":"7.7.20. gru"},{"refs":[{"id":"ref-for-mloperand-shape\u2463\u2460"},{"id":"ref-for-mloperand-shape\u2463\u2461"},{"id":"ref-for-mloperand-shape\u2463\u2462"},{"id":"ref-for-mloperand-shape\u2463\u2463"},{"id":"ref-for-mloperand-shape\u2463\u2464"},{"id":"ref-for-mloperand-shape\u2463\u2465"},{"id":"ref-for-mloperand-shape\u2463\u2466"}],"title":"7.7.21. gruCell"},{"refs":[{"id":"ref-for-mloperand-shape\u2463\u2467"},{"id":"ref-for-mloperand-shape\u2463\u2468"},{"id":"ref-for-mloperand-shape\u2464\u24ea"},{"id":"ref-for-mloperand-shape\u2464\u2460"},{"id":"ref-for-mloperand-shape\u2464\u2461"},{"id":"ref-for-mloperand-shape\u2464\u2462"}],"title":"7.7.24. instanceNormalization"},{"refs":[{"id":"ref-for-mloperand-shape\u2464\u2463"},{"id":"ref-for-mloperand-shape\u2464\u2464"},{"id":"ref-for-mloperand-shape\u2464\u2465"}],"title":"7.7.25. layerNormalization"},{"refs":[{"id":"ref-for-mloperand-shape\u2464\u2466"},{"id":"ref-for-mloperand-shape\u2464\u2467"},{"id":"ref-for-mloperand-shape\u2464\u2468"},{"id":"ref-for-mloperand-shape\u2465\u24ea"},{"id":"ref-for-mloperand-shape\u2465\u2460"},{"id":"ref-for-mloperand-shape\u2465\u2461"},{"id":"ref-for-mloperand-shape\u2465\u2462"},{"id":"ref-for-mloperand-shape\u2465\u2463"},{"id":"ref-for-mloperand-shape\u2465\u2464"},{"id":"ref-for-mloperand-shape\u2465\u2465"}],"title":"7.7.28. lstm"},{"refs":[{"id":"ref-for-mloperand-shape\u2465\u2466"},{"id":"ref-for-mloperand-shape\u2465\u2467"},{"id":"ref-for-mloperand-shape\u2465\u2468"},{"id":"ref-for-mloperand-shape\u2466\u24ea"},{"id":"ref-for-mloperand-shape\u2466\u2460"},{"id":"ref-for-mloperand-shape\u2466\u2461"},{"id":"ref-for-mloperand-shape\u2466\u2462"},{"id":"ref-for-mloperand-shape\u2466\u2463"},{"id":"ref-for-mloperand-shape\u2466\u2464"}],"title":"7.7.29. lstmCell"},{"refs":[{"id":"ref-for-mloperand-shape\u2466\u2465"},{"id":"ref-for-mloperand-shape\u2466\u2466"}],"title":"7.7.30. matmul"},{"refs":[{"id":"ref-for-mloperand-shape\u2466\u2467"}],"title":"7.7.31. pad"},{"refs":[{"id":"ref-for-mloperand-shape\u2466\u2468"}],"title":"7.7.32. Pooling operations"},{"refs":[{"id":"ref-for-mloperand-shape\u2467\u24ea"},{"id":"ref-for-mloperand-shape\u2467\u2460"}],"title":"7.7.33. prelu"},{"refs":[{"id":"ref-for-mloperand-shape\u2467\u2461"}],"title":"7.7.34. Reduction operations"},{"refs":[{"id":"ref-for-mloperand-shape\u2467\u2462"}],"title":"7.7.36. resample2d"},{"refs":[{"id":"ref-for-mloperand-shape\u2467\u2463"}],"title":"7.7.37. reshape"},{"refs":[{"id":"ref-for-mloperand-shape\u2467\u2464"},{"id":"ref-for-mloperand-shape\u2467\u2465"}],"title":"7.7.39. slice"},{"refs":[{"id":"ref-for-mloperand-shape\u2467\u2466"},{"id":"ref-for-mloperand-shape\u2467\u2467"},{"id":"ref-for-mloperand-shape\u2467\u2468"},{"id":"ref-for-mloperand-shape\u2468\u24ea"}],"title":"7.7.43. split"},{"refs":[{"id":"ref-for-mloperand-shape\u2468\u2460"}],"title":"7.7.45. transpose"},{"refs":[{"id":"ref-for-mloperand-shape\u2468\u2461"},{"id":"ref-for-mloperand-shape\u2468\u2462"},{"id":"ref-for-mloperand-shape\u2468\u2463"}],"title":"7.7.47. where"}],"url":"#mloperand-shape"},
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