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2025-06-12 7b72ac13a83764a662159d4a49b7fffb90476ecb

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/**
 * @license
 * Copyright 2021 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 { SparseSegmentMean } from '@tensorflow/tfjs-core';
import { sparseSegmentReductionImplCPU } from '../kernel_utils/shared';
export function sparseSegmentMean(args) {
    const { inputs, backend } = args;
    const { data, indices, segmentIds } = inputs;
    if (data.shape.length < 1) {
        throw new Error(`Data should be at least 1 dimensional but received scalar`);
    }
    if (indices.shape.length !== 1) {
        throw new Error(`Indices should be a vector but received shape
              ${indices.shape}`);
    }
    if (segmentIds.shape.length !== 1) {
        throw new Error(`Segment ids should be a vector but received shape
              ${segmentIds.shape}`);
    }
    const $data = backend.readSync(data.dataId);
    const $indices = backend.readSync(indices.dataId);
    const $segmentIds = backend.readSync(segmentIds.dataId);
    const [outputData, outputDataShape] = sparseSegmentReductionImplCPU($data, data.shape, data.dtype, $indices, $segmentIds, true);
    return backend.makeTensorInfo(outputDataShape, data.dtype, outputData);
}
export const sparseSegmentMeanConfig = {
    kernelName: SparseSegmentMean,
    backendName: 'webgl',
    kernelFunc: sparseSegmentMean,
};
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