/// <amd-module name="@tensorflow/tfjs-core/dist/ops/losses/compute_weighted_loss" />
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/**
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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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import { Tensor } from '../../tensor';
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import { TensorLike } from '../../types';
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import { Reduction } from '../loss_ops_utils';
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/**
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* Computes the weighted loss between two tensors.
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*
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* @param losses Tensor of shape `[batch_size, d1, ..., dN]`.
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* @param weights Tensor whose rank is either 0, or the same rank as
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* `losses`, and must be broadcastable to `losses` (i.e., all
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* dimensions must be either `1`, or the same as the corresponding
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* `losses` dimension).
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*
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* @doc {heading: 'Training', subheading: 'Losses', namespace: 'losses'}
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*/
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declare function computeWeightedLoss_<T extends Tensor, O extends Tensor>(losses: T | TensorLike, weights?: Tensor | TensorLike, reduction?: Reduction): O;
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export declare const computeWeightedLoss: typeof computeWeightedLoss_;
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export {};
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