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topk.ts
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topk.ts
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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 {TopK, TopKAttrs, TopKInputs} from '../kernel_names';
import {NamedAttrMap} from '../kernel_registry';
import {Tensor} from '../tensor';
import {NamedTensorMap} from '../tensor_types';
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 < 0) {
throw new Error(`'k' passed to topk() must be >= 0 but got ${k}`);
}
if (k > lastDim) {
throw new Error(
`'k' passed to topk() must be <= the last dimension (${lastDim}) ` +
`but got ${k}`);
}
const inputs: TopKInputs = {x: $x};
const attrs: TopKAttrs = {k, sorted};
const [values, indices] = ENGINE.runKernel(
TopK, inputs as unknown as NamedTensorMap,
attrs as unknown as NamedAttrMap) as [T, T];
return {values, indices};
}
export const topk = /* @__PURE__ */ op({topk_});