/// 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 {};