/**

* @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 {Concat, ConcatAttrs, ConcatInputs} from '../kernel_names';

import {NamedAttrMap} from '../kernel_registry';

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

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

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

import {TensorLike} from '../types';

import {assert} from '../util';

import {clone} from './clone';

import {op} from './operation';

/**

* Concatenates a list of `tf.Tensor`s along a given axis.

*

* The tensors ranks and types must match, and their sizes must match in all

* dimensions except `axis`.

*

* Also available are stricter rank-specific methods that assert that

* `tensors` are of the given rank:

* - `tf.concat1d`

* - `tf.concat2d`

* - `tf.concat3d`

* - `tf.concat4d`

*

* Except `tf.concat1d` (which does not have axis param), all methods have

* same signature as this method.

*

* ```js

* const a = tf.tensor1d([1, 2]);

* const b = tf.tensor1d([3, 4]);

* a.concat(b).print(); // or a.concat(b)

* ```

*

* ```js

* const a = tf.tensor1d([1, 2]);

* const b = tf.tensor1d([3, 4]);

* const c = tf.tensor1d([5, 6]);

* tf.concat([a, b, c]).print();

* ```

*

* ```js

* const a = tf.tensor2d([[1, 2], [10, 20]]);

* const b = tf.tensor2d([[3, 4], [30, 40]]);

* const axis = 1;

* tf.concat([a, b], axis).print();

* ```

* @param tensors A list of tensors to concatenate.

* @param axis The axis to concatenate along. Defaults to 0 (the first dim).

*

* @doc {heading: 'Tensors', subheading: 'Slicing and Joining'}

*/

function concat_<T extends Tensor>(tensors: Array<T|TensorLike>, axis = 0): T {

}

export const concat = /* @__PURE__ */ op({concat_});