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