/**
|
* @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.
|
* =============================================================================
|
*/
|
/// <amd-module name="@tensorflow/tfjs-core/dist/ops/squared_difference" />
|
import { Tensor } from '../tensor';
|
import { TensorLike } from '../types';
|
/**
|
* Returns (a - b) * (a - b) element-wise.
|
* Supports broadcasting.
|
*
|
* ```js
|
* const a = tf.tensor1d([1, 4, 3, 16]);
|
* const b = tf.tensor1d([1, 2, 9, 4]);
|
*
|
* a.squaredDifference(b).print(); // or tf.squaredDifference(a, b)
|
* ```
|
*
|
* ```js
|
* // Broadcast squared difference a with b.
|
* const a = tf.tensor1d([2, 4, 6, 8]);
|
* const b = tf.scalar(5);
|
*
|
* a.squaredDifference(b).print(); // or tf.squaredDifference(a, b)
|
* ```
|
*
|
* @param a The first tensor.
|
* @param b The second tensor. Must have the same type as `a`.
|
*
|
* @doc {heading: 'Operations', subheading: 'Arithmetic'}
|
*/
|
declare function squaredDifference_<T extends Tensor>(a: Tensor | TensorLike, b: Tensor | TensorLike): T;
|
export declare const squaredDifference: typeof squaredDifference_;
|
export {};
|