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