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 { Tensor, Tensor1D } from '../tensor';
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18 | import { Rank, TensorLike } from '../types';
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19 | /**
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20 | * Batch normalization.
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21 | *
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22 | * As described in
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23 | * [http://arxiv.org/abs/1502.03167](http://arxiv.org/abs/1502.03167).
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24 | *
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25 | * Mean, variance, scale, and offset can be of two shapes:
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26 | * - The same shape as the input.
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27 | * - In the common case, the depth dimension is the last dimension of x, so
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28 | * the values would be an `tf.Tensor1D` of shape [depth].
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29 | *
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30 | * Also available are stricter rank-specific methods with the same signature
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31 | * as this method that assert that parameters passed are of given rank
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32 | * - `tf.batchNorm2d`
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33 | * - `tf.batchNorm3d`
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34 | * - `tf.batchNorm4d`
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35 | *
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36 | * @param x The input Tensor.
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37 | * @param mean A mean Tensor.
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38 | * @param variance A variance Tensor.
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39 | * @param offset An offset Tensor.
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40 | * @param scale A scale Tensor.
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41 | * @param varianceEpsilon A small float number to avoid dividing by 0.
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42 | *
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43 | * @doc {heading: 'Operations', subheading: 'Normalization'}
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44 | */
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45 | declare function batchNorm_<R extends Rank>(x: Tensor<R> | TensorLike, mean: Tensor<R> | Tensor1D | TensorLike, variance: Tensor<R> | Tensor1D | TensorLike, offset?: Tensor<R> | Tensor1D | TensorLike, scale?: Tensor<R> | Tensor1D | TensorLike, varianceEpsilon?: number): Tensor<R>;
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46 | export declare const batchNorm: typeof batchNorm_;
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47 | export {};
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