/**
 * @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-converter/dist/executor/tensor_list" />
import { DataType, Tensor } from '@tensorflow/tfjs-core';
/**
 * TensorList stores a container of `tf.Tensor` objects, which are accessible
 * via tensors field.
 *
 * In order to get a copy of the underlying list, use the copy method:
 * ```
 *    TensorList b = a.copy();
 *    b.tensors().pushBack(t);  // This does not modify a.tensors().
 * ```
 *
 * Note that this is not a deep copy: the memory locations of the underlying
 * tensors will still point to the same locations of the corresponding tensors
 * in the original.
 */
export declare class TensorList {
    readonly tensors: Tensor[];
    readonly elementShape: number | number[];
    readonly elementDtype: DataType;
    readonly idTensor: Tensor;
    maxNumElements: number;
    get id(): number;
    /**
     *
     * @param tensors list of tensors
     * @param elementShape shape of each tensor, this can be a single number (any
     * shape is allowed) or partial shape (dim = -1).
     * @param elementDtype data type of each tensor
     * @param maxNumElements The maximum allowed size of `tensors`. Defaults to -1
     *   meaning that the size of `tensors` is unbounded.
     */
    constructor(tensors: Tensor[], elementShape: number | number[], elementDtype: DataType, maxNumElements?: number);
    /**
     * Get a new TensorList containing a copy of the underlying tensor container.
     */
    copy(): TensorList;
    /**
     * Dispose the tensors and idTensor and clear the tensor list.
     */
    clearAndClose(keepIds?: Set<number>): void;
    /**
     * The size of the tensors in the tensor list.
     */
    size(): number;
    /**
     * Return a tensor that stacks a list of rank-R tf.Tensors into one rank-(R+1)
     * tf.Tensor.
     * @param elementShape shape of each tensor
     * @param elementDtype data type of each tensor
     * @param numElements the number of elements to stack
     */
    stack(elementShape: number[], elementDtype: DataType, numElements?: number): Tensor;
    /**
     * Pop a tensor from the end of the list.
     * @param elementShape shape of the tensor
     * @param elementDtype data type of the tensor
     */
    popBack(elementShape: number[], elementDtype: DataType): Tensor;
    /**
     * Push a tensor to the end of the list.
     * @param tensor Tensor to be pushed.
     */
    pushBack(tensor: Tensor): void;
    /**
     * Update the size of the list.
     * @param size the new size of the list.
     */
    resize(size: number): TensorList;
    /**
     * Retrieve the element at the provided index
     * @param elementShape shape of the tensor
     * @param elementDtype dtype of the tensor
     * @param elementIndex index of the tensor
     */
    getItem(elementIndex: number, elementShape: number[], elementDtype: DataType): Tensor;
    /**
     * Set the tensor at the index
     * @param elementIndex index of the tensor
     * @param tensor the tensor to be inserted into the list
     */
    setItem(elementIndex: number, tensor: Tensor): void;
    /**
     * Return selected values in the TensorList as a stacked Tensor. All of
     * selected values must have been written and their shapes must all match.
     * @param indices indices of tensors to gather
     * @param elementDtype output tensor dtype
     * @param elementShape output tensor element shape
     */
    gather(indices: number[], elementDtype: DataType, elementShape: number[]): Tensor;
    /**
     * Return the values in the TensorList as a concatenated Tensor.
     * @param elementDtype output tensor dtype
     * @param elementShape output tensor element shape
     */
    concat(elementDtype: DataType, elementShape: number[]): Tensor;
}
/**
 * Creates a TensorList which, when stacked, has the value of tensor.
 * @param tensor from tensor
 * @param elementShape output tensor element shape
 */
export declare function fromTensor(tensor: Tensor, elementShape: number[], elementDtype: DataType): TensorList;
/**
 * Return a TensorList of the given size with empty elements.
 * @param elementShape the shape of the future elements of the list
 * @param elementDtype the desired type of elements in the list
 * @param numElements the number of elements to reserve
 * @param maxNumElements the maximum number of elements in th list
 */
export declare function reserve(elementShape: number[], elementDtype: DataType, numElements: number, maxNumElements: number): TensorList;
/**
 * Put tensors at specific indices of a stacked tensor into a TensorList.
 * @param indices list of indices on how to scatter the tensor.
 * @param tensor input tensor.
 * @param elementShape the shape of the future elements of the list
 * @param numElements the number of elements to scatter
 */
export declare function scatter(tensor: Tensor, indices: number[], elementShape: number[], numElements?: number): TensorList;
/**
 * Split the values of a Tensor into a TensorList.
 * @param length the lengths to use when splitting value along
 *    its first dimension.
 * @param tensor the tensor to split.
 * @param elementShape the shape of the future elements of the list
 */
export declare function split(tensor: Tensor, length: number[], elementShape: number[]): TensorList;