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GatherNd.ts
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GatherNd.ts
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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 {backend_util, GatherNd, GatherNdInputs, KernelConfig, KernelFunc, Rank, TensorInfo, TypedArray, util} from '@tensorflow/tfjs-core';
import {MathBackendCPU} from '../backend_cpu';
import {gatherNdImpl} from './GatherNd_Impl';
export function gatherNd(
args: {inputs: GatherNdInputs, backend: MathBackendCPU}): TensorInfo {
const {inputs, backend} = args;
const {params, indices} = inputs;
const paramsSize = util.sizeFromShape(params.shape);
const indicesShape = indices.shape;
const sliceRank = indicesShape[indicesShape.length - 1];
const [resultShape, numSlices, sliceSize, strides] =
backend_util.prepareAndValidate(params, indices);
if (numSlices === 0) {
return backend.makeTensorInfo(resultShape, params.dtype, []);
}
const indicesData = backend.data.get(indices.dataId).values as TypedArray;
const paramsBuf = backend.bufferSync<Rank, 'float32'>(params);
const outBuf = gatherNdImpl(
indicesData, paramsBuf, params.dtype, numSlices, sliceRank, sliceSize,
strides, params.shape, paramsSize);
return backend.makeTensorInfo(resultShape, params.dtype, outBuf.values);
}
export const gatherNdConfig: KernelConfig = {
kernelName: GatherNd,
backendName: 'cpu',
kernelFunc: gatherNd as unknown as KernelFunc
};