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Context-based graph execution methods for different threading models. #257

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merged 13 commits into from
Apr 30, 2022
Merged

Context-based graph execution methods for different threading models. #257

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e287ced
Context-based graph execution methods for different threading models.
wchao1115 Mar 10, 2022
4bad865
Fixing multiple refs on Promise type.
wchao1115 Mar 10, 2022
1aeabca
Fix up over-aggressive search/replace.
wchao1115 Mar 10, 2022
8dff216
Remove `MLCommandEncoder` and simplify `MLContext` creation with params.
wchao1115 Mar 28, 2022
26d5bc1
Fix missing graph param
wchao1115 Mar 28, 2022
3feadd7
Fix build break due to merge conflict.
wchao1115 Mar 28, 2022
6a24927
Fix build break: Disambiguate the WebIDL link to {{Promise}} definition.
wchao1115 Mar 28, 2022
ef9262b
GPU support on sync execution (limited to worker thread). Default con…
wchao1115 Apr 18, 2022
3710e71
Remove undefined `MLResource` type.
wchao1115 Apr 18, 2022
ff7e4f2
Remove references to undefined MLInput type.
wchao1115 Apr 18, 2022
59bbbe9
Remove outdated note section in the computeAsync description. Further…
wchao1115 Apr 21, 2022
0ed918f
Add a note section describing when graph initialization occurs on a d…
wchao1115 Apr 22, 2022
0ea819d
Adjust some wordings on the note section of `MLGraphBuilder.build` me…
wchao1115 Apr 22, 2022
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Expand Up @@ -989,6 +989,10 @@ interface MLGraphBuilder {
};
</script>

<div class="note">
The {{MLGraphBuilder}}.{{MLGraphBuilder/build()}} method compiles the graph builder state up to the specified output operands into a compiled graph according to the type of {{MLContext}} backing it. When the {{[[contextType]]}} of the {{MLContext}} is set to [=default-context|default=] with the {{MLContextOptions}}.{{deviceType}} set to [=device-type-gpu|gpu=], the compiled graph is initialized right before the {{MLGraphBuilder/build()}} method call returns. This initialization stage is important for optimal performance of the subsequent graph executions. See [[#api-mlcommandencoder-graph-initialization]] for more detail.
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</div>

### batchNormalization ### {#api-mlgraphbuilder-batchnorm}
Normalize the tensor values of input features across the batch dimension using [[Batch-Normalization]]. For each input feature, the mean and variance values of that feature supplied in this calculation as parameters are previously computed across the batch dimension of the input during the model training phase of this operation.
<script type=idl>
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