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2025-02-12 ea42ff3ebee1eeb3fb29423aa848a249441db81c

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/**
 * @license
 * Copyright 2020 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 { OneHot, util } from '@tensorflow/tfjs-core';
import { assertNotComplex } from '../cpu_util';
export function oneHot(args) {
    const { inputs, backend, attrs } = args;
    const { indices } = inputs;
    const { dtype, depth, onValue, offValue } = attrs;
    assertNotComplex(indices, 'oneHot');
    const indicesSize = util.sizeFromShape(indices.shape);
    const res = new Float32Array(indicesSize * depth);
    res.fill(offValue);
    const indicesVal = backend.data.get(indices.dataId).values;
    for (let event = 0; event < indicesSize; ++event) {
        if (indicesVal[event] >= 0 && indicesVal[event] < depth) {
            res[event * depth + indicesVal[event]] = onValue;
        }
    }
    return backend.makeTensorInfo([...indices.shape, depth], dtype, res);
}
export const oneHotConfig = {
    kernelName: OneHot,
    backendName: 'cpu',
    kernelFunc: oneHot
};
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