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/// <amd-module name="@tensorflow/tfjs-core/dist/ops/gather_nd" />
import { Tensor } from '../tensor';
import { TensorLike } from '../types';
/**
* Gather slices from input tensor into a Tensor with shape specified by
* `indices`.
*
* `indices` is an K-dimensional integer tensor, best thought of as a
* (K-1)-dimensional tensor of indices into input, where each element defines a
* slice of input:
* output[\\(i_0, ..., i_{K-2}\\)] = input[indices[\\(i_0, ..., i_{K-2}\\)]]
* Whereas in `tf.gather`, `indices` defines slices into the first dimension of
* input, in `tf.gatherND`, `indices` defines slices into the first N dimensions
* of input, where N = indices.shape[-1].
* The last dimension of indices can be at most the rank of input:
* indices.shape[-1] <= input.rank
* The last dimension of `indices` corresponds to elements
* (if indices.shape[-1] == input.rank) or slices
* (if indices.shape[-1] < input.rank) along dimension indices.shape[-1] of
* input.
* The output tensor has shape
* indices.shape[:-1] + input.shape[indices.shape[-1]:]
* Note that on CPU, if an out of bound index is found, an error is returned. On
* GPU, if an out of bound index is found, a 0 is stored in the corresponding
* output value.
* ```js
* const indices = tf.tensor2d([0, 1, 1, 0], [2,2], 'int32');
* const input = tf.tensor2d([9, 10, 11, 12], [2, 2]);
* tf.gatherND(input, indices).print() // [10, 11]
* ```
* @param x The tensor from which to gather values.
* @param indices Index tensor, must be of type int32.
* @doc {heading: 'Operations', subheading: 'Slicing and Joining'}
*/
declare function gatherND_(x: Tensor | TensorLike, indices: Tensor | TensorLike): Tensor;
export declare const gatherND: typeof gatherND_;
export {};