/**
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* @license
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* Copyright 2020 Google LLC. 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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/// <amd-module name="@tensorflow/tfjs-core/dist/ops/moments" />
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import { Tensor } from '../tensor';
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import { TensorLike } from '../types';
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/**
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* Calculates the mean and variance of `x`. The mean and variance are
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* calculated by aggregating the contents of `x` across `axes`. If `x` is
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* 1-D and `axes = [0]` this is just the mean and variance of a vector.
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*
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* @param x The input tensor.
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* @param axis The dimension(s) along with to compute mean and
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* variance. By default it reduces all dimensions.
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* @param keepDims If true, the moments have the same dimensionality as the
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* input.
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* @return An object with two keys: `mean` and `variance`.
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*
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* @doc {heading: 'Operations', subheading: 'Normalization'}
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*/
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declare function moments_(x: Tensor | TensorLike, axis?: number | number[], keepDims?: boolean): {
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mean: Tensor;
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variance: Tensor;
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};
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export declare const moments: typeof moments_;
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export {};
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