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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @license * Copyright 2018 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ import {ENGINE} from '../engine'; import {NumericTensor, Tensor} from '../tensor'; import {convertToTensor} from '../tensor_util_env'; import {TensorLike} from '../types'; import {op} from './operation'; /** * Finds the values and indices of the `k` largest entries along the last * dimension. * * If the input is a vector (rank=1), finds the k largest entries in the vector * and outputs their values and indices as vectors. Thus values[j] is the j-th * largest entry in input, and its index is indices[j]. * For higher rank inputs, computes the top k entries along the last dimension. * * If two elements are equal, the lower-index element appears first. * * ```js * const a = tf.tensor2d([[1, 5], [4, 3]]); * const {values, indices} = tf.topk(a); * values.print(); * indices.print(); * ``` * @param x 1-D or higher `tf.Tensor` with last dimension being at least `k`. * @param k Number of top elements to look for along the last dimension. * @param sorted If true, the resulting `k` elements will be sorted by the * values in descending order. */ /** @doc {heading: 'Operations', subheading: 'Evaluation'} */ function topk_<T extends Tensor>( x: T|TensorLike, k = 1, sorted = true): {values: T, indices: T} { const $x = convertToTensor(x, 'x', 'topk'); if ($x.rank === 0) { throw new Error('topk() expects the input to be of rank 1 or higher'); } const lastDim = $x.shape[$x.shape.length - 1]; if (k > lastDim) { throw new Error( `'k' passed to topk() must be <= the last dimension (${lastDim}) ` + `but got ${k}`); } const [values, indices] = ENGINE.runKernel(b => b.topk($x as NumericTensor, k, sorted), {$x}); return {values, indices} as {values: T, indices: T}; } export const topk = op({topk_});