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wchao1115 committed Apr 4, 2020
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<div class="head">
<p data-fill-with="logo"></p>
<h1 class="p-name no-ref" id="title">Web Neural Network API</h1>
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<h2 class="no-num no-toc no-ref heading settled" id="subtitle"><span class="content">Draft Community Group Report, <time class="dt-updated" datetime="2020-03-24">24 March 2020</time></span></h2>
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<h2 class="no-num no-toc no-ref heading settled" id="subtitle"><span class="content">Draft Community Group Report, <time class="dt-updated" datetime="2020-03-18">18 March 2020</time></span></h2>
>>>>>>> Update CompilationPreference to follow WebGL convention for context creation. Update the code sample to show how a certain compilation could fail such as when the model uses data type not supported by the hardware, and how to recover from the failure.
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<h2 class="no-num no-toc no-ref heading settled" id="subtitle"><span class="content">Draft Community Group Report, <time class="dt-updated" datetime="2020-04-01">1 April 2020</time></span></h2>
>>>>>>> Update according to feedbacks and to align more closely with WebGL.
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<h2 class="no-num no-toc no-ref heading settled" id="subtitle"><span class="content">Draft Community Group Report, <time class="dt-updated" datetime="2020-04-03">3 April 2020</time></span></h2>
>>>>>>> Add the 'default' option for PowerPreference.
<h2 class="no-num no-toc no-ref heading settled" id="subtitle"><span class="content">Draft Community Group Report, <time class="dt-updated" datetime="2020-04-04">4 April 2020</time></span></h2>
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<dl>
<dt>This version:
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<li><a href="#dom-powerpreference-high-performance">"high-performance"</a><span>, in §3.6</span>
<li><a href="#dom-neuralnetworkcontext-input">input(desc)</a><span>, in §3.5</span>
<li><a href="#dom-operandtype-int32">"int32"</a><span>, in §3.3</span>
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<li><a href="#dom-compilationpreference-low-power">"low-power"</a><span>, in §3.6</span>
<li><a href="#dom-neuralnetworkcontext-matmul">matmul(a, b)</a><span>, in §3.5.3</span>
<li><a href="#dom-navigator-ml">ml</a><span>, in §3.1</span>
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<li><a href="#dom-powerpreference-low-power">"low-power"</a><span>, in §3.6</span>
>>>>>>> Update according to feedbacks and to align more closely with WebGL.
<li><a href="#dom-neuralnetworkcontext-matmul">matmul(a, b)</a><span>, in §3.5.3</span>
<li><a href="#ml">ML</a><span>, in §3.2</span>
<li><a href="#dom-navigator-ml">ml</a><span>, in §3.1</span>
<li><a href="#model">Model</a><span>, in §3.6</span>
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};

<c- b>interface</c-> <a href="#ml"><code><c- g>ML</c-></code></a> {
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<a class="n" data-link-type="idl-name" href="#neuralnetworkcontext" id="ref-for-neuralnetworkcontext⑤"><c- n>NeuralNetworkContext</c-></a> <a href="#dom-ml-getneuralnetworkcontext"><code><c- g>getNeuralNetworkContext</c-></code></a>();
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<a class="n" data-link-type="idl-name" href="#neuralnetworkcontext"><c- n>NeuralNetworkContext</c-></a> <a href="#dom-ml-getneuralnetworkcontext"><code><c- g>getNeuralNetworkContext</c-></code></a>();
>>>>>>> Update according to feedbacks and to align more closely with WebGL.
};

<c- b>enum</c-> <a href="#enumdef-operandlayout"><code><c- g>OperandLayout</c-></code></a> {
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<c- b>interface</c-> <a href="#neuralnetworkcontext"><code><c- g>NeuralNetworkContext</c-></code></a> {
// Create an Operand object that represents a model input.
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<a class="n" data-link-type="idl-name" href="#operand" id="ref-for-operand②②"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-input"><code><c- g>input</c-></code></a>(<a class="n" data-link-type="idl-name" href="#dictdef-operanddescriptor" id="ref-for-dictdef-operanddescriptor②"><c- n>OperandDescriptor</c-></a> <a href="#dom-neuralnetworkcontext-input-desc-desc"><code><c- g>desc</c-></code></a>);

// Create an Operand object that represents a model constant.
<a class="n" data-link-type="idl-name" href="#operand" id="ref-for-operand①①⓪"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-constant"><code><c- g>constant</c-></code></a>(<a class="n" data-link-type="idl-name" href="#dictdef-operanddescriptor" id="ref-for-dictdef-operanddescriptor①①"><c- n>OperandDescriptor</c-></a> <a href="#dom-neuralnetworkcontext-constant-desc-value-desc"><code><c- g>desc</c-></code></a>, <a class="n" data-link-type="idl-name" href="https://heycam.github.io/webidl/#ArrayBufferView" id="ref-for-ArrayBufferView③"><c- n>ArrayBufferView</c-></a> <a href="#dom-neuralnetworkcontext-constant-desc-value-value"><code><c- g>value</c-></code></a>);
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<a class="n" data-link-type="idl-name" href="#operand"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-input"><code><c- g>input</c-></code></a>(<a class="n" data-link-type="idl-name" href="#dictdef-operanddescriptor"><c- n>OperandDescriptor</c-></a> <a href="#dom-neuralnetworkcontext-input-desc-desc"><code><c- g>desc</c-></code></a>);

// Create an Operand object that represents a model constant.
<a class="n" data-link-type="idl-name" href="#operand"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-constant"><code><c- g>constant</c-></code></a>(<a class="n" data-link-type="idl-name" href="#dictdef-operanddescriptor"><c- n>OperandDescriptor</c-></a> <a href="#dom-neuralnetworkcontext-constant-desc-value-desc"><code><c- g>desc</c-></code></a>, <a class="n" data-link-type="idl-name" href="https://heycam.github.io/webidl/#ArrayBufferView"><c- n>ArrayBufferView</c-></a> <a href="#dom-neuralnetworkcontext-constant-desc-value-value"><code><c- g>value</c-></code></a>);
>>>>>>> Update according to feedbacks and to align more closely with WebGL.

// Create a Model object by identifying output operands.
<c- b>Promise</c->&lt;<a class="n" data-link-type="idl-name" href="#model"><c- n>Model</c-></a>> <a href="#dom-neuralnetworkcontext-createmodel"><code><c- g>createModel</c-></code></a>(<c- b>sequence</c->&lt;<a class="n" data-link-type="idl-name" href="#operand"><c- n>Operand</c-></a>> <a href="#dom-neuralnetworkcontext-createmodel-outputs-outputs"><code><c- g>outputs</c-></code></a>);
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<c- b>optional</c-> <a class="n" data-link-type="idl-name" href="#enumdef-operandlayout"><c- n>OperandLayout</c-></a> <a href="#dom-neuralnetworkcontext-conv2d-input-filter-padding-strides-dilations-layout-layout"><code><c- g>layout</c-></code></a> = "nchw");
};

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<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#neuralnetworkcontext" id="ref-for-neuralnetworkcontext③①"><c- g>NeuralNetworkContext</c-></a> {
<a class="n" data-link-type="idl-name" href="#operand" id="ref-for-operand①②①"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-matmul"><code><c- g>matmul</c-></code></a>(<a class="n" data-link-type="idl-name" href="#operand" id="ref-for-operand①③①"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-matmul-a-b-a"><code><c- g>a</c-></code></a>, <a class="n" data-link-type="idl-name" href="#operand" id="ref-for-operand①④①"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-matmul-a-b-b"><code><c- g>b</c-></code></a>);
<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#neuralnetworkcontext"><c- g>NeuralNetworkContext</c-></a> {
<a class="n" data-link-type="idl-name" href="#operand"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-matmul"><code><c- g>matmul</c-></code></a>(<a class="n" data-link-type="idl-name" href="#operand"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-matmul-a-b-a"><code><c- g>a</c-></code></a>, <a class="n" data-link-type="idl-name" href="#operand"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-matmul-a-b-b"><code><c- g>b</c-></code></a>);
};

<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#neuralnetworkcontext" id="ref-for-neuralnetworkcontext④①"><c- g>NeuralNetworkContext</c-></a> {
// Create an Operand object that represents the result of an element-wise
// binary multiplication operation with input operands a and b.
<a class="n" data-link-type="idl-name" href="#operand" id="ref-for-operand①⑧①"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-mul"><code><c- g>mul</c-></code></a>(<a class="n" data-link-type="idl-name" href="#operand" id="ref-for-operand①⑨①"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-mul-a-b-a"><code><c- g>a</c-></code></a>, <a class="n" data-link-type="idl-name" href="#operand" id="ref-for-operand②⓪①"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-mul-a-b-b"><code><c- g>b</c-></code></a>);
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<c- b>partial</c-> <c- b>interface</c-> <a class="idl-code" data-link-type="interface" href="#neuralnetworkcontext"><c- g>NeuralNetworkContext</c-></a> {
// Create an Operand object that represents the result of an element-wise
// binary multiplication operation with input operands a and b.
<a class="n" data-link-type="idl-name" href="#operand"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-mul"><code><c- g>mul</c-></code></a>(<a class="n" data-link-type="idl-name" href="#operand"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-mul-a-b-a"><code><c- g>a</c-></code></a>, <a class="n" data-link-type="idl-name" href="#operand"><c- n>Operand</c-></a> <a href="#dom-neuralnetworkcontext-mul-a-b-b"><code><c- g>b</c-></code></a>);
>>>>>>> Update according to feedbacks and to align more closely with WebGL.
};

<c- b>enum</c-> <a href="#enumdef-powerpreference"><code><c- g>PowerPreference</c-></code></a> {
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