/**

* @license

* Copyright 2022 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.

* =============================================================================

*/

import {ENGINE} from '../engine';

import {TensorScatterUpdate, TensorScatterUpdateAttrs, TensorScatterUpdateInputs} from '../kernel_names';

import {NamedAttrMap} from '../kernel_registry';

import {Tensor} from '../tensor';

import {NamedTensorMap} from '../tensor_types';

import {convertToTensor} from '../tensor_util_env';

import {Rank, TensorLike} from '../types';

import {op} from './operation';

import * as scatter_nd_util from './scatter_nd_util';

/**

* Creates a new tensor by applying sparse updates to individual

* values or slices to the passed in tensor according to

* indices. This operator is the similar to scatterNd op, except that the

* udpates are scattered on an existing tensor (as opposed to a zero-tensor).

*

* If indices contains duplicates, then we pick the last update for the index.

*

* If an out of bound index is found on CPU, an error is returned.

*

* Warning: There are some GPU specific semantics for this operation.

* - If an out of bound index is found, the index is ignored.

* - The order in which updates are applied is nondeterministic, so the output

* will be nondeterministic if indices contains duplicates.

* ```js

* const shape = [8];

* const tensor = tf.ones(shape);

* const indices = tf.tensor2d([4, 3, 1, 7], [4, 1], 'int32');

* const updates = tf.tensor1d([9, 10, 11, 12]);

*

* tf.tensorScatterUpdate(tensor, indices, updates).print();

* //[1, 11, 1, 10, 9, 1, 1, 12]

* ```

*

* @param tensor A Tensor. Tensor to copy/update.

* @param indices The tensor contains the indices into the output tensor, must

* have at least 2 axes: (num_updates, index_depth).

* @param updates The tensor contains the value for the indices.

*

* @doc {heading: 'Operations', subheading: 'Slicing and Joining'}

*/

function tensorScatterUpdate_<R extends Rank>(

}

export const tensorScatterUpdate = op({tensorScatterUpdate_});