/**
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* @license
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* Copyright 2021 Google LLC. All Rights Reserved.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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import { SparseSegmentMean } from '@tensorflow/tfjs-core';
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import { sparseSegmentReductionImplCPU } from '../kernel_utils/shared';
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export function sparseSegmentMean(args) {
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const { inputs, backend } = args;
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const { data, indices, segmentIds } = inputs;
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if (data.shape.length < 1) {
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throw new Error(`Data should be at least 1 dimensional but received scalar`);
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}
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if (indices.shape.length !== 1) {
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throw new Error(`Indices should be a vector but received shape
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${indices.shape}`);
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}
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if (segmentIds.shape.length !== 1) {
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throw new Error(`Segment ids should be a vector but received shape
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${segmentIds.shape}`);
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}
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const $data = backend.readSync(data.dataId);
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const $indices = backend.readSync(indices.dataId);
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const $segmentIds = backend.readSync(segmentIds.dataId);
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const [outputData, outputDataShape] = sparseSegmentReductionImplCPU($data, data.shape, data.dtype, $indices, $segmentIds, true);
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return backend.makeTensorInfo(outputDataShape, data.dtype, outputData);
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}
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export const sparseSegmentMeanConfig = {
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kernelName: SparseSegmentMean,
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backendName: 'webgl',
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kernelFunc: sparseSegmentMean,
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};
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