@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
/**
* @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 { ENGINE } from '../engine';
import { LogicalAnd } from '../kernel_names';
import { convertToTensor } from '../tensor_util_env';
import { assertAndGetBroadcastShape } from './broadcast_util';
import { op } from './operation';
/**
* Returns the truth value of `a AND b` element-wise. Supports broadcasting.
*
* ```js
* const a = tf.tensor1d([false, false, true, true], 'bool');
* const b = tf.tensor1d([false, true, false, true], 'bool');
*
* a.logicalAnd(b).print();
* ```
*
* @param a The first input tensor. Must be of dtype bool.
* @param b The second input tensor. Must be of dtype bool.
*
* @doc {heading: 'Operations', subheading: 'Logical'}
*/
function logicalAnd_(a, b) {
const $a = convertToTensor(a, 'a', 'logicalAnd', 'bool');
const $b = convertToTensor(b, 'b', 'logicalAnd', 'bool');
assertAndGetBroadcastShape($a.shape, $b.shape);
const inputs = { a: $a, b: $b };
return ENGINE.runKernel(LogicalAnd, inputs);
}
export const logicalAnd = op({ logicalAnd_ });
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