/**
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* @license
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* Copyright 2023 Google LLC.
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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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/// <amd-module name="@tensorflow/tfjs-core/dist/ops/bitwise_and" />
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import { Tensor } from '../tensor';
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import { Rank } from '../types';
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/**
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* Bitwise `AND` operation for input tensors.
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*
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* Given two input tensors, returns a new tensor
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* with the `AND` calculated values.
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*
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* The method supports int32 values
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*
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*
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* ```js
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* const x = tf.tensor1d([0, 5, 3, 14], 'int32');
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* const y = tf.tensor1d([5, 0, 7, 11], 'int32');
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* tf.bitwiseAnd(x, y).print();
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* ```
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*
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* @param x The input tensor to be calculated.
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* @param y The input tensor to be calculated.
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*
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* @doc {heading: 'Operations', subheading: 'Logical'}
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*/
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declare function bitwiseAnd_<R extends Rank>(x: Tensor, y: Tensor): Tensor<R>;
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export declare const bitwiseAnd: typeof bitwiseAnd_;
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export {};
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