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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Remove outdated note section in the computeAsync description.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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7 changes: 4 additions & 3 deletions explainer.md
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Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,7 @@ const bufferB = new Float32Array(4).fill(0.8);
const bufferC = new Float32Array(4);
const inputs = {'A': bufferA, 'B': bufferB};
const outputs = {'C': bufferC};
graph.compute(inputs, outputs);
context.compute(graph, inputs, outputs);
// The computed result of [[1, 1], [1, 1]] is in the buffer associated with
// the output operand.
console.log('Output value: ' + bufferC);
Expand Down Expand Up @@ -99,12 +99,13 @@ There are many important [application use cases](https://webmachinelearning.gith
export class NSNet2 {
constructor() {
this.graph = null;
this.context = null;
this.frameSize = 161;
this.hiddenSize = 400;
}

async build(baseUrl, batchSize, frames) {
const context = navigator.ml.createContext();
this.context = navigator.ml.createContext();
const builder = new MLGraphBuilder(context);
// Create constants by loading pre-trained data from .npy files.
const weight172 = await buildConstantByNpy(builder, baseUrl + '172.npy');
Expand Down Expand Up @@ -153,7 +154,7 @@ export class NSNet2 {
'gru94': gru94Buffer,
'gru157': gru157Buffer
};
return this.graph.compute(inputs, outputs);
return this.context.compute(this.graph, inputs, outputs);
}
}
```
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