@tensorflow/tfjs-core/dist/io/model_management.d.ts

Hardware-accelerated JavaScript library for machine intelligence

/**
 * @license
 * Copyright 2018 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-core/dist/io/model_management" />
import { ModelArtifactsInfo, ModelStoreManager } from './types';
export declare class ModelStoreManagerRegistry {
    private static instance;
    private managers;
    private constructor();
    private static getInstance;
    /**
     * Register a save-handler router.
     *
     * @param saveRouter A function that maps a URL-like string onto an instance
     * of `IOHandler` with the `save` method defined or `null`.
     */
    static registerManager(scheme: string, manager: ModelStoreManager): void;
    static getManager(scheme: string): ModelStoreManager;
    static getSchemes(): string[];
}
/**
 * List all models stored in registered storage mediums.
 *
 * For a web browser environment, the registered mediums are Local Storage and
 * IndexedDB.
 *
 * ```js
 * // First create and save a model.
 * const model = tf.sequential();
 * model.add(tf.layers.dense(
 *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
 * await model.save('localstorage://demo/management/model1');
 *
 * // Then list existing models.
 * console.log(JSON.stringify(await tf.io.listModels()));
 *
 * // Delete the model.
 * await tf.io.removeModel('localstorage://demo/management/model1');
 *
 * // List models again.
 * console.log(JSON.stringify(await tf.io.listModels()));
 * ```
 *
 * @returns A `Promise` of a dictionary mapping URLs of existing models to
 * their model artifacts info. URLs include medium-specific schemes, e.g.,
 *   'indexeddb://my/model/1'. Model artifacts info include type of the
 * model's topology, byte sizes of the topology, weights, etc.
 *
 * @doc {
 *   heading: 'Models',
 *   subheading: 'Management',
 *   namespace: 'io',
 *   ignoreCI: true
 * }
 */
declare function listModels(): Promise<{
    [url: string]: ModelArtifactsInfo;
}>;
/**
 * Remove a model specified by URL from a registered storage medium.
 *
 * ```js
 * // First create and save a model.
 * const model = tf.sequential();
 * model.add(tf.layers.dense(
 *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
 * await model.save('localstorage://demo/management/model1');
 *
 * // Then list existing models.
 * console.log(JSON.stringify(await tf.io.listModels()));
 *
 * // Delete the model.
 * await tf.io.removeModel('localstorage://demo/management/model1');
 *
 * // List models again.
 * console.log(JSON.stringify(await tf.io.listModels()));
 * ```
 *
 * @param url A URL to a stored model, with a scheme prefix, e.g.,
 *   'localstorage://my-model-1', 'indexeddb://my/model/2'.
 * @returns ModelArtifactsInfo of the deleted model (if and only if deletion
 *   is successful).
 * @throws Error if deletion fails, e.g., if no model exists at `path`.
 *
 * @doc {
 *   heading: 'Models',
 *   subheading: 'Management',
 *   namespace: 'io',
 *   ignoreCI: true
 * }
 */
declare function removeModel(url: string): Promise<ModelArtifactsInfo>;
/**
 * Copy a model from one URL to another.
 *
 * This function supports:
 *
 * 1. Copying within a storage medium, e.g.,
 *    `tf.io.copyModel('localstorage://model-1', 'localstorage://model-2')`
 * 2. Copying between two storage mediums, e.g.,
 *    `tf.io.copyModel('localstorage://model-1', 'indexeddb://model-1')`
 *
 * ```js
 * // First create and save a model.
 * const model = tf.sequential();
 * model.add(tf.layers.dense(
 *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
 * await model.save('localstorage://demo/management/model1');
 *
 * // Then list existing models.
 * console.log(JSON.stringify(await tf.io.listModels()));
 *
 * // Copy the model, from Local Storage to IndexedDB.
 * await tf.io.copyModel(
 *     'localstorage://demo/management/model1',
 *     'indexeddb://demo/management/model1');
 *
 * // List models again.
 * console.log(JSON.stringify(await tf.io.listModels()));
 *
 * // Remove both models.
 * await tf.io.removeModel('localstorage://demo/management/model1');
 * await tf.io.removeModel('indexeddb://demo/management/model1');
 * ```
 *
 * @param sourceURL Source URL of copying.
 * @param destURL Destination URL of copying.
 * @returns ModelArtifactsInfo of the copied model (if and only if copying
 *   is successful).
 * @throws Error if copying fails, e.g., if no model exists at `sourceURL`, or
 *   if `oldPath` and `newPath` are identical.
 *
 * @doc {
 *   heading: 'Models',
 *   subheading: 'Management',
 *   namespace: 'io',
 *   ignoreCI: true
 * }
 */
declare function copyModel(sourceURL: string, destURL: string): Promise<ModelArtifactsInfo>;
/**
 * Move a model from one URL to another.
 *
 * This function supports:
 *
 * 1. Moving within a storage medium, e.g.,
 *    `tf.io.moveModel('localstorage://model-1', 'localstorage://model-2')`
 * 2. Moving between two storage mediums, e.g.,
 *    `tf.io.moveModel('localstorage://model-1', 'indexeddb://model-1')`
 *
 * ```js
 * // First create and save a model.
 * const model = tf.sequential();
 * model.add(tf.layers.dense(
 *     {units: 1, inputShape: [10], activation: 'sigmoid'}));
 * await model.save('localstorage://demo/management/model1');
 *
 * // Then list existing models.
 * console.log(JSON.stringify(await tf.io.listModels()));
 *
 * // Move the model, from Local Storage to IndexedDB.
 * await tf.io.moveModel(
 *     'localstorage://demo/management/model1',
 *     'indexeddb://demo/management/model1');
 *
 * // List models again.
 * console.log(JSON.stringify(await tf.io.listModels()));
 *
 * // Remove the moved model.
 * await tf.io.removeModel('indexeddb://demo/management/model1');
 * ```
 *
 * @param sourceURL Source URL of moving.
 * @param destURL Destination URL of moving.
 * @returns ModelArtifactsInfo of the copied model (if and only if copying
 *   is successful).
 * @throws Error if moving fails, e.g., if no model exists at `sourceURL`, or
 *   if `oldPath` and `newPath` are identical.
 *
 * @doc {
 *   heading: 'Models',
 *   subheading: 'Management',
 *   namespace: 'io',
 *   ignoreCI: true
 * }
 */
declare function moveModel(sourceURL: string, destURL: string): Promise<ModelArtifactsInfo>;
export { moveModel, copyModel, removeModel, listModels };