/**

* @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 {Diag, DiagInputs} from '../kernel_names';

import {Tensor} from '../tensor';

import {NamedTensorMap} from '../tensor_types';

import {convertToTensor} from '../tensor_util_env';

import {op} from './operation';

/**

* Returns a diagonal tensor with given diagonal values.

*

* Given a diagonal, this operation returns a tensor with the diagonal and

* everything else padded with zeros.

*

* Assume the input has dimensions `[D1,..., Dk]`, then the output is a tensor

* of rank 2k with dimensions `[D1,..., Dk, D1,..., Dk]`

*

* ```js

* const x = tf.tensor1d([1, 2, 3, 4]);

*

* tf.diag(x).print()

* ```

* ```js

* const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [4, 2])

*

* tf.diag(x).print()

* ```

* @param x The input tensor.

*

* @doc {heading: 'Tensors', subheading: 'Creation'}

*/

function diag_(x: Tensor): Tensor {

}

export const diag = /* @__PURE__ */ op({diag_});