/**
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* @license
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* Copyright 2018 Google Inc. 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 { Tensor } from '../tensor';
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import { Rank, ShapeMap, TensorLike } from '../types';
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/**
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* Creates a new tensor by applying sparse updates to individual
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* values or slices within a zero tensor of the given shape tensor according to
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* indices. This operator is the inverse of the `tf.gatherND` operator which
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* extracts values or slices from a given tensor.
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*
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* ```js
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* const indices = tf.tensor2d([4, 3, 1, 7], [4, 1], 'int32');
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* const updates = tf.tensor1d([9, 10, 11, 12]);
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* const shape = [8];
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* tf.scatterND(indices, updates, shape).print() //[0, 11, 0, 10, 9, 0, 0, 12]
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* ```
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*
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* @param indices The tensor contains the indices into the output tensor.
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* @param updates The tensor contains the value for the indices.
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* @param shape: The shape of the output tensor.
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*/
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/** @doc {heading: 'Operations', subheading: 'Slicing and Joining'} */
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declare function scatterND_<R extends Rank>(indices: Tensor | TensorLike, updates: Tensor | TensorLike, shape: ShapeMap[R]): Tensor<R>;
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export declare const scatterND: typeof scatterND_;
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export {};
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