@tensorflow/tfjs-core/dist/ops/split.d.ts

Hardware-accelerated JavaScript library for machine intelligence

/// <amd-module name="@tensorflow/tfjs-core/dist/ops/split" />
import { Tensor } from '../tensor';
import { TensorLike } from '../types';
/**
 * Splits a `tf.Tensor` into sub tensors.
 *
 * If `numOrSizeSplits` is a number, splits `x` along dimension `axis`
 * into `numOrSizeSplits` smaller tensors.
 * Requires that `numOrSizeSplits` evenly divides `x.shape[axis]`.
 *
 * If `numOrSizeSplits` is a number array, splits `x` into
 * `numOrSizeSplits.length` pieces. The shape of the `i`-th piece has the
 * same size as `x` except along dimension `axis` where the size is
 * `numOrSizeSplits[i]`.
 *
 * ```js
 * const x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7, 8], [2, 4]);
 * const [a, b] = tf.split(x, 2, 1);
 * a.print();
 * b.print();
 *
 * const [c, d, e] = tf.split(x, [1, 2, 1], 1);
 * c.print();
 * d.print();
 * e.print();
 * ```
 *
 * @param x The input tensor to split.
 * @param numOrSizeSplits Either an integer indicating the number of
 * splits along the axis or an array of integers containing the sizes of
 * each output tensor along the axis. If a number then it must evenly divide
 * `x.shape[axis]`; otherwise the sum of sizes must match `x.shape[axis]`.
 * Can contain one -1 indicating that dimension is to be inferred.
 * @param axis The dimension along which to split. Defaults to 0 (the first
 * dim).
 *
 * @doc {heading: 'Tensors', subheading: 'Slicing and Joining'}
 */
declare function split_<T extends Tensor>(x: Tensor | TensorLike, numOrSizeSplits: number[] | number, axis?: number): T[];
export declare const split: typeof split_;
export {};