/// <amd-module name="@tensorflow/tfjs-core/dist/ops/min" />
import { Tensor } from '../tensor';
import { TensorLike } from '../types';
/**
 * Computes the minimum value from the input.
 *
 * Reduces the input along the dimensions given in `axes`. Unless `keepDims`
 * is true, the rank of the array is reduced by 1 for each entry in `axes`.
 * If `keepDims` is true, the reduced dimensions are retained with length 1.
 * If `axes` has no entries, all dimensions are reduced, and an array with a
 * single element is returned.
 *
 * ```js
 * const x = tf.tensor1d([1, 2, 3]);
 *
 * x.min().print();  // or tf.min(x)
 * ```
 *
 * ```js
 * const x = tf.tensor2d([1, 2, 3, 4], [2, 2]);
 *
 * const axis = 1;
 * x.min(axis).print();  // or tf.min(x, axis)
 * ```
 *
 * @param x The input Tensor.
 * @param axis The dimension(s) to reduce. By default it reduces
 *     all dimensions.
 * @param keepDims If true, retains reduced dimensions with size 1.
 *
 * @doc {heading: 'Operations', subheading: 'Reduction'}
 */
declare function min_<T extends Tensor>(x: Tensor | TensorLike, axis?: number | number[], keepDims?: boolean): T;
export declare const min: typeof min_;
export {};