/**
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* @license
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* Copyright 2018 Google Inc. All Rights Reserved.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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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 dropout.
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*
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* ```js
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* const x = tf.tensor1d([1, 2, 2, 1]);
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* const rate = 0.75;
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* const output = tf.dropout(x, rate);
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* output.print();
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* ```
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*
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* @param x A floating point Tensor or TensorLike.
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* @param rate A float in the range [0, 1). The probability that each element
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* of x is discarded.
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* @param noiseShape An array of numbers of type int32, representing the
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* shape for randomly generated keep/drop flags. If the noiseShape has null
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* value, it will be automatically replaced with the x's relative dimension
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* size. Optional.
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* @param seed Used to create random seeds. Optional.
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* @returns A Tensor of the same shape of x.
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*/
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/** @doc {heading: 'Operations', subheading: 'Dropout'} */
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declare function dropout_(x: Tensor | TensorLike, rate: number, noiseShape?: number[], seed?: number | string): Tensor;
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export declare const dropout: typeof dropout_;
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export {};
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