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chenyc

2025-06-12 7b72ac13a83764a662159d4a49b7fffb90476ecb

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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 { MaxPoolWithArgmax } from '@tensorflow/tfjs-core';
import { backend_util, util } from '@tensorflow/tfjs-core';
import { maxPoolWithArgmaxImpl } from './MaxPoolWithArgmax_impl';
export const maxPoolWithArgmaxConfig = {
    kernelName: MaxPoolWithArgmax,
    backendName: 'webgl',
    kernelFunc: ({ inputs, attrs, backend }) => {
        const { x } = inputs;
        const { filterSize, strides, pad, includeBatchInIndex } = attrs;
        const webglBackend = backend;
        util.assert(x.shape.length === 4, () => `Error in maxPool: input must be rank 4 but got rank ${x.shape.length}.`);
        const dilations = [1, 1];
        util.assert(backend_util.eitherStridesOrDilationsAreOne(strides, dilations), () => 'Error in maxPool: Either strides or dilations must be 1. ' +
            `Got strides ${strides} and dilations '${dilations}'`);
        const convInfo = backend_util.computePool2DInfo(x.shape, filterSize, strides, dilations, pad);
        const [result, indexes] = maxPoolWithArgmaxImpl(x, includeBatchInIndex, convInfo, webglBackend);
        return [result, indexes];
    }
};
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