@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 { RealDiv } from '../kernel_names';
import { makeTypesMatch } from '../tensor_util';
import { convertToTensor } from '../tensor_util_env';
import { floorDiv } from './floorDiv';
import { op } from './operation';
/**
* Divides two `tf.Tensor`s element-wise, A / B. Supports broadcasting.
*
* ```js
* const a = tf.tensor1d([1, 4, 9, 16]);
* const b = tf.tensor1d([1, 2, 3, 4]);
*
* a.div(b).print(); // or tf.div(a, b)
* ```
*
* ```js
* // Broadcast div a with b.
* const a = tf.tensor1d([2, 4, 6, 8]);
* const b = tf.scalar(2);
*
* a.div(b).print(); // or tf.div(a, b)
* ```
*
* @param a The first tensor as the numerator.
* @param b The second tensor as the denominator. Must have the same dtype as
* `a`.
*
* @doc {heading: 'Operations', subheading: 'Arithmetic'}
*/
function div_(a, b) {
let $a = convertToTensor(a, 'a', 'div');
let $b = convertToTensor(b, 'b', 'div');
[$a, $b] = makeTypesMatch($a, $b);
if ($a.dtype === 'int32' && $b.dtype === 'int32') {
return floorDiv($a, $b);
}
const inputs = { a: $a, b: $b };
const attrs = {};
// tslint:disable-next-line: no-unnecessary-type-assertion
return ENGINE.runKernel(RealDiv, inputs, attrs);
}
export const div = op({ div_ });
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