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@tensorflow/tfjs-core

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Hardware-accelerated JavaScript library for machine intelligence

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/** * @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/http" /> import { IORouter } from './router_registry'; import { IOHandler, LoadOptions, ModelArtifacts, SaveResult } from './types'; export declare class HTTPRequest implements IOHandler { protected readonly path: string; protected readonly requestInit: RequestInit; private readonly fetch; private readonly weightUrlConverter; readonly DEFAULT_METHOD = "POST"; static readonly URL_SCHEME_REGEX: RegExp; private readonly weightPathPrefix; private readonly loadOptions; constructor(path: string, loadOptions?: LoadOptions); save(modelArtifacts: ModelArtifacts): Promise<SaveResult>; private loadModelJSON; /** * Load model artifacts via HTTP request(s). * * See the documentation to `tf.io.http` for details on the saved * artifacts. * * @returns The loaded model artifacts (if loading succeeds). */ load(): Promise<ModelArtifacts>; private loadStream; private getWeightUrls; private loadWeights; } /** * Extract the prefix and suffix of the url, where the prefix is the path before * the last file, and suffix is the search params after the last file. * ``` * const url = 'http://tfhub.dev/model/1/tensorflowjs_model.pb?tfjs-format=file' * [prefix, suffix] = parseUrl(url) * // prefix = 'http://tfhub.dev/model/1/' * // suffix = '?tfjs-format=file' * ``` * @param url the model url to be parsed. */ export declare function parseUrl(url: string): [string, string]; export declare function isHTTPScheme(url: string): boolean; export declare const httpRouter: IORouter; /** * Creates an IOHandler subtype that sends model artifacts to HTTP server. * * An HTTP request of the `multipart/form-data` mime type will be sent to the * `path` URL. The form data includes artifacts that represent the topology * and/or weights of the model. In the case of Keras-style `tf.Model`, two * blobs (files) exist in form-data: * - A JSON file consisting of `modelTopology` and `weightsManifest`. * - A binary weights file consisting of the concatenated weight values. * These files are in the same format as the one generated by * [tfjs_converter](https://js.tensorflow.org/tutorials/import-keras.html). * * The following code snippet exemplifies the client-side code that uses this * function: * * ```js * const model = tf.sequential(); * model.add( * tf.layers.dense({units: 1, inputShape: [100], activation: 'sigmoid'})); * * const saveResult = await model.save(tf.io.http( * 'http://model-server:5000/upload', {requestInit: {method: 'PUT'}})); * console.log(saveResult); * ``` * * If the default `POST` method is to be used, without any custom parameters * such as headers, you can simply pass an HTTP or HTTPS URL to `model.save`: * * ```js * const saveResult = await model.save('http://model-server:5000/upload'); * ``` * * The following GitHub Gist * https://gist.github.com/dsmilkov/1b6046fd6132d7408d5257b0976f7864 * implements a server based on [flask](https://github.com/pallets/flask) that * can receive the request. Upon receiving the model artifacts via the request, * this particular server reconstitutes instances of [Keras * Models](https://keras.io/models/model/) in memory. * * * @param path A URL path to the model. * Can be an absolute HTTP path (e.g., * 'http://localhost:8000/model-upload)') or a relative path (e.g., * './model-upload'). * @param requestInit Request configurations to be used when sending * HTTP request to server using `fetch`. It can contain fields such as * `method`, `credentials`, `headers`, `mode`, etc. See * https://developer.mozilla.org/en-US/docs/Web/API/Request/Request * for more information. `requestInit` must not have a body, because the * body will be set by TensorFlow.js. File blobs representing the model * topology (filename: 'model.json') and the weights of the model (filename: * 'model.weights.bin') will be appended to the body. If `requestInit` has a * `body`, an Error will be thrown. * @param loadOptions Optional configuration for the loading. It includes the * following fields: * - weightPathPrefix Optional, this specifies the path prefix for weight * files, by default this is calculated from the path param. * - fetchFunc Optional, custom `fetch` function. E.g., in Node.js, * the `fetch` from node-fetch can be used here. * - onProgress Optional, progress callback function, fired periodically * before the load is completed. * @returns An instance of `IOHandler`. * * @doc { * heading: 'Models', * subheading: 'Loading', * namespace: 'io', * ignoreCI: true * } */ export declare function http(path: string, loadOptions?: LoadOptions): IOHandler; /** * Deprecated. Use `tf.io.http`. * @param path * @param loadOptions */ export declare function browserHTTPRequest(path: string, loadOptions?: LoadOptions): IOHandler;