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1/**
2 * @license
3 * Copyright 2020 Google LLC. All Rights Reserved.
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 * =============================================================================
16 */
17import { ENGINE } from '../engine';
18import { Sub } from '../kernel_names';
19import { makeTypesMatch } from '../tensor_util';
20import { convertToTensor } from '../tensor_util_env';
21import { op } from './operation';
22/**
23 * Subtracts two `tf.Tensor`s element-wise, A - B. Supports broadcasting.
24 *
25 * ```js
26 * const a = tf.tensor1d([10, 20, 30, 40]);
27 * const b = tf.tensor1d([1, 2, 3, 4]);
28 *
29 * a.sub(b).print(); // or tf.sub(a, b)
30 * ```
31 *
32 * ```js
33 * // Broadcast subtract a with b.
34 * const a = tf.tensor1d([10, 20, 30, 40]);
35 * const b = tf.scalar(5);
36 *
37 * a.sub(b).print(); // or tf.sub(a, b)
38 * ```
39 * @param a The first `tf.Tensor` to subtract from.
40 * @param b The second `tf.Tensor` to be subtracted. Must have the same dtype as
41 * `a`.
42 *
43 * @doc {heading: 'Operations', subheading: 'Arithmetic'}
44 */
45function sub_(a, b) {
46 let $a = convertToTensor(a, 'a', 'sub');
47 let $b = convertToTensor(b, 'b', 'sub');
48 [$a, $b] = makeTypesMatch($a, $b);
49 const inputs = { a: $a, b: $b };
50 return ENGINE.runKernel(Sub, inputs);
51}
52export const sub = op({ sub_ });
53//# sourceMappingURL=sub.js.map
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