@tensorflow/tfjs-core/dist/ops/moments.d.ts

Hardware-accelerated JavaScript library for machine intelligence

/**
 * @license
 * Copyright 2020 Google LLC. All Rights Reserved.
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 * =============================================================================
 */
/// <amd-module name="@tensorflow/tfjs-core/dist/ops/moments" />
import { Tensor } from '../tensor';
import { TensorLike } from '../types';
/**
 * Calculates the mean and variance of `x`. The mean and variance are
 * calculated by aggregating the contents of `x` across `axes`. If `x` is
 * 1-D and `axes = [0]` this is just the mean and variance of a vector.
 *
 * @param x The input tensor.
 * @param axis The dimension(s) along with to compute mean and
 *     variance. By default it reduces all dimensions.
 * @param keepDims If true, the moments have the same dimensionality as the
 *     input.
 * @return An object with two keys: `mean` and `variance`.
 *
 * @doc {heading: 'Operations', subheading: 'Normalization'}
 */
declare function moments_(x: Tensor | TensorLike, axis?: number | number[], keepDims?: boolean): {
    mean: Tensor;
    variance: Tensor;
};
export declare const moments: typeof moments_;
export {};