///
import { Tensor } from '../tensor';
import { TensorLike } from '../types';
/**
* 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 concate along. Defaults to 0 (the first dim).
*
* @doc {heading: 'Tensors', subheading: 'Slicing and Joining'}
*/
declare function concat_(tensors: Array, axis?: number): T;
export declare const concat: typeof concat_;
export {};