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1/**
2 * @license
3 * Copyright 2020 Google LLC. All Rights Reserved.
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 * =============================================================================
16 */
17/// <amd-module name="@tensorflow/tfjs-core/dist/ops/multinomial" />
18import { Tensor1D, Tensor2D } from '../tensor';
19import { TensorLike } from '../types';
20/**
21 * Creates a `tf.Tensor` with values drawn from a multinomial distribution.
22 *
23 * ```js
24 * const probs = tf.tensor([.75, .25]);
25 * tf.multinomial(probs, 3).print();
26 * ```
27 *
28 * @param logits 1D array with unnormalized log-probabilities, or
29 * 2D array of shape `[batchSize, numOutcomes]`. See the `normalized`
30 * parameter.
31 * @param numSamples Number of samples to draw for each row slice.
32 * @param seed The seed number.
33 * @param normalized Whether the provided `logits` are normalized true
34 * probabilities (sum to 1). Defaults to false.
35 * @return 1D array of shape `[numSamples]`, or 2D array of shape
36 * `[batchSize, numSamples]`, depending on the rank of the input.
37 *
38 * @doc {heading: 'Tensors', subheading: 'Random'}
39 */
40declare function multinomial_(logits: Tensor1D | Tensor2D | TensorLike, numSamples: number, seed?: number, normalized?: boolean): Tensor1D | Tensor2D;
41export declare const multinomial: typeof multinomial_;
42export {};