@tensorflow/tfjs-backend-wasm
Version:
This package adds a WebAssembly backend to TensorFlow.js. It currently supports the following models from our [models](https://github.com/tensorflow/tfjs-models) repo: - BlazeFace - BodyPix - CocoSSD - Face landmarks detection - HandPose - KNN classifier
43 lines • 5.4 kB
JavaScript
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
import { ClipByValue } from '@tensorflow/tfjs-core';
let wasmClip;
function setup(backend) {
wasmClip = backend.wasm.cwrap(ClipByValue, null /* void */, [
'number',
'number',
'number',
'number' // out_id
]);
}
function clip(args) {
const { inputs, backend, attrs } = args;
const { x } = inputs;
const { clipValueMin, clipValueMax } = attrs;
const xId = backend.dataIdMap.get(x.dataId).id;
const out = backend.makeOutput(x.shape, x.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
wasmClip(xId, clipValueMin, clipValueMax, outId);
return out;
}
export const clipByValueConfig = {
kernelName: ClipByValue,
backendName: 'wasm',
setupFunc: setup,
kernelFunc: clip
};
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