/**
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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/one_hot" />
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import { Tensor } from '../tensor';
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import { DataType, TensorLike } from '../types';
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/**
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* Creates a one-hot `tf.Tensor`. The locations represented by `indices` take
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* value `onValue` (defaults to 1), while all other locations take value
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* `offValue` (defaults to 0). If `indices` is rank `R`, the output has rank
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* `R+1` with the last axis of size `depth`.
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* `indices` used to encode prediction class must start from 0. For example,
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* if you have 3 classes of data, class 1 should be encoded as 0, class 2
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* should be 1, and class 3 should be 2.
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*
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* ```js
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* tf.oneHot(tf.tensor1d([0, 1], 'int32'), 3).print();
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* ```
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*
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* @param indices `tf.Tensor` of indices with dtype `int32`. Indices must
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* start from 0.
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* @param depth The depth of the one hot dimension.
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* @param onValue A number used to fill in the output when the index matches
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* the location.
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* @param offValue A number used to fill in the output when the index does
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* not match the location.
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* @param dtype The dtype of the output tensor, default to 'int32'.
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*
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* @doc {heading: 'Tensors', subheading: 'Creation'}
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*/
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declare function oneHot_(indices: Tensor | TensorLike, depth: number, onValue?: number, offValue?: number, dtype?: DataType): Tensor;
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export declare const oneHot: typeof oneHot_;
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export {};
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