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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 { Tensor } from '../tensor';
18/**
19 * Returns a diagonal tensor with a given diagonal values.
20 *
21 * Given a diagonal, this operation returns a tensor with the diagonal and
22 * everything else padded with zeros.
23 *
24 * Assume the input has dimensions `[D1,..., Dk]`, then the output is a tensor
25 * of rank 2k with dimensions `[D1,..., Dk, D1,..., Dk]`
26 *
27 * ```js
28 * const x = tf.tensor1d([1, 2, 3, 4]);
29 *
30 * tf.diag(x).print()
31 * ```
32 * ```js
33 * const x = tf.tensor1d([1, 2, 3, 4, 5, 6, 6, 8], [4, 2])
34 *
35 * tf.diag(x).print()
36 * ```
37 * @param x The input tensor.
38 *
39 * @doc {heading: 'Tensors', subheading: 'Creation'}
40 */
41declare function diag_(x: Tensor): Tensor;
42export declare const diag: typeof diag_;
43export {};