/**
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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 { TensorLike } from '../types';
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/**
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* Apply boolean mask to tensor.
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*
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* ```js
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* const tensor = tf.tensor2d([1, 2, 3, 4, 5, 6], [3, 2]);
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* const mask = tf.tensor1d([1, 0, 1], 'bool');
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* const result = await tf.booleanMaskAsync(tensor, mask);
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* result.print();
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* ```
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*
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* @param tensor N-D tensor.
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* @param mask K-D boolean tensor, K <= N and K must be known statically.
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* @param axis A 0-D int Tensor representing the axis in tensor to mask from.
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* By default, axis is 0 which will mask from the first dimension.
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* Otherwise K + axis <= N.
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*/
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/** @doc {heading: 'Tensors', subheading: 'Slicing and Joining'} */
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declare function booleanMaskAsync_(tensor: Tensor | TensorLike, mask: Tensor | TensorLike, axis?: number): Promise<Tensor>;
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export declare const booleanMaskAsync: typeof booleanMaskAsync_;
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export {};
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