/**
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* @license
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* Copyright 2018 Google LLC. All Rights Reserved.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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/**
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* IOHandler implementations based on HTTP requests in the web browser.
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*
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* Uses [`fetch`](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API).
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*/
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import {env} from '../environment';
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import {assert} from '../util';
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import {concatenateArrayBuffers, getModelArtifactsInfoForJSON} from './io_utils';
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import {IORouter, IORouterRegistry} from './router_registry';
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import {IOHandler, LoadOptions, ModelArtifacts, ModelJSON, OnProgressCallback, SaveResult, WeightsManifestConfig, WeightsManifestEntry} from './types';
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import {loadWeightsAsArrayBuffer} from './weights_loader';
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const OCTET_STREAM_MIME_TYPE = 'application/octet-stream';
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const JSON_TYPE = 'application/json';
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export class HTTPRequest implements IOHandler {
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protected readonly path: string;
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protected readonly requestInit: RequestInit;
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private readonly fetch: Function;
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readonly DEFAULT_METHOD = 'POST';
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static readonly URL_SCHEME_REGEX = /^https?:\/\//;
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private readonly weightPathPrefix: string;
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private readonly onProgress: OnProgressCallback;
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constructor(path: string, loadOptions?: LoadOptions) {
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if (loadOptions == null) {
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loadOptions = {};
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}
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this.weightPathPrefix = loadOptions.weightPathPrefix;
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this.onProgress = loadOptions.onProgress;
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if (loadOptions.fetchFunc != null) {
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assert(
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typeof loadOptions.fetchFunc === 'function',
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() => 'Must pass a function that matches the signature of ' +
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'`fetch` (see ' +
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'https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)');
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this.fetch = loadOptions.fetchFunc;
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} else {
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this.fetch = env().platform.fetch;
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}
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assert(
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path != null && path.length > 0,
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() => 'URL path for http must not be null, undefined or ' +
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'empty.');
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if (Array.isArray(path)) {
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assert(
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path.length === 2,
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() => 'URL paths for http must have a length of 2, ' +
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`(actual length is ${path.length}).`);
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}
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this.path = path;
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if (loadOptions.requestInit != null &&
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loadOptions.requestInit.body != null) {
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throw new Error(
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'requestInit is expected to have no pre-existing body, but has one.');
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}
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this.requestInit = loadOptions.requestInit || {};
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}
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async save(modelArtifacts: ModelArtifacts): Promise<SaveResult> {
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if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
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throw new Error(
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'BrowserHTTPRequest.save() does not support saving model topology ' +
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'in binary formats yet.');
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}
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const init = Object.assign({method: this.DEFAULT_METHOD}, this.requestInit);
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init.body = new FormData();
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const weightsManifest: WeightsManifestConfig = [{
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paths: ['./model.weights.bin'],
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weights: modelArtifacts.weightSpecs,
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}];
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const modelTopologyAndWeightManifest: ModelJSON = {
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modelTopology: modelArtifacts.modelTopology,
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format: modelArtifacts.format,
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generatedBy: modelArtifacts.generatedBy,
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convertedBy: modelArtifacts.convertedBy,
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userDefinedMetadata: modelArtifacts.userDefinedMetadata,
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weightsManifest
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};
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init.body.append(
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'model.json',
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new Blob(
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[JSON.stringify(modelTopologyAndWeightManifest)],
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{type: JSON_TYPE}),
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'model.json');
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if (modelArtifacts.weightData != null) {
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init.body.append(
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'model.weights.bin',
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new Blob([modelArtifacts.weightData], {type: OCTET_STREAM_MIME_TYPE}),
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'model.weights.bin');
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}
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const response = await this.fetch(this.path, init);
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if (response.ok) {
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return {
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modelArtifactsInfo: getModelArtifactsInfoForJSON(modelArtifacts),
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responses: [response],
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};
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} else {
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throw new Error(
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`BrowserHTTPRequest.save() failed due to HTTP response status ` +
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`${response.status}.`);
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}
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}
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/**
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* Load model artifacts via HTTP request(s).
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*
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* See the documentation to `tf.io.http` for details on the saved
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* artifacts.
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*
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* @returns The loaded model artifacts (if loading succeeds).
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*/
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async load(): Promise<ModelArtifacts> {
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const modelConfigRequest = await this.fetch(this.path, this.requestInit);
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if (!modelConfigRequest.ok) {
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throw new Error(
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`Request to ${this.path} failed with status code ` +
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`${modelConfigRequest.status}. Please verify this URL points to ` +
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`the model JSON of the model to load.`);
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}
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let modelConfig: ModelJSON;
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try {
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modelConfig = await modelConfigRequest.json();
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} catch (e) {
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let message = `Failed to parse model JSON of response from ${this.path}.`;
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// TODO(nsthorat): Remove this after some time when we're comfortable that
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// .pb files are mostly gone.
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if (this.path.endsWith('.pb')) {
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message += ' Your path contains a .pb file extension. ' +
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'Support for .pb models have been removed in TensorFlow.js 1.0 ' +
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'in favor of .json models. You can re-convert your Python ' +
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'TensorFlow model using the TensorFlow.js 1.0 conversion scripts ' +
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'or you can convert your.pb models with the \'pb2json\'' +
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'NPM script in the tensorflow/tfjs-converter repository.';
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} else {
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message += ' Please make sure the server is serving valid ' +
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'JSON for this request.';
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}
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throw new Error(message);
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}
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const modelTopology = modelConfig.modelTopology;
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const weightsManifest = modelConfig.weightsManifest;
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const generatedBy = modelConfig.generatedBy;
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const convertedBy = modelConfig.convertedBy;
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const format = modelConfig.format;
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const userDefinedMetadata = modelConfig.userDefinedMetadata;
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// We do not allow both modelTopology and weightsManifest to be missing.
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if (modelTopology == null && weightsManifest == null) {
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throw new Error(
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`The JSON from HTTP path ${this.path} contains neither model ` +
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`topology or manifest for weights.`);
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}
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let weightSpecs: WeightsManifestEntry[];
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let weightData: ArrayBuffer;
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if (weightsManifest != null) {
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const results = await this.loadWeights(weightsManifest);
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[weightSpecs, weightData] = results;
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}
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return {
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modelTopology,
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weightSpecs,
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weightData,
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userDefinedMetadata,
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generatedBy,
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convertedBy,
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format
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};
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}
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private async loadWeights(weightsManifest: WeightsManifestConfig):
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Promise<[WeightsManifestEntry[], ArrayBuffer]> {
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const weightPath = Array.isArray(this.path) ? this.path[1] : this.path;
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const [prefix, suffix] = parseUrl(weightPath);
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const pathPrefix = this.weightPathPrefix || prefix;
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const weightSpecs = [];
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for (const entry of weightsManifest) {
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weightSpecs.push(...entry.weights);
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}
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const fetchURLs: string[] = [];
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weightsManifest.forEach(weightsGroup => {
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weightsGroup.paths.forEach(path => {
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fetchURLs.push(pathPrefix + path + suffix);
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});
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});
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const buffers = await loadWeightsAsArrayBuffer(fetchURLs, {
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requestInit: this.requestInit,
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fetchFunc: this.fetch,
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onProgress: this.onProgress
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});
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return [weightSpecs, concatenateArrayBuffers(buffers)];
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}
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}
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/**
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* Extract the prefix and suffix of the url, where the prefix is the path before
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* the last file, and suffix is the search params after the last file.
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* ```
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* const url = 'http://tfhub.dev/model/1/tensorflowjs_model.pb?tfjs-format=file'
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* [prefix, suffix] = parseUrl(url)
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* // prefix = 'http://tfhub.dev/model/1/'
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* // suffix = '?tfjs-format=file'
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* ```
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* @param url the model url to be parsed.
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*/
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export function parseUrl(url: string): [string, string] {
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const lastSlash = url.lastIndexOf('/');
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const lastSearchParam = url.lastIndexOf('?');
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const prefix = url.substring(0, lastSlash);
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const suffix =
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lastSearchParam > lastSlash ? url.substring(lastSearchParam) : '';
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return [prefix + '/', suffix];
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}
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export function isHTTPScheme(url: string): boolean {
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return url.match(HTTPRequest.URL_SCHEME_REGEX) != null;
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}
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export const httpRouter: IORouter =
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(url: string, onProgress?: OnProgressCallback) => {
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if (typeof fetch === 'undefined') {
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// `http` uses `fetch` or `node-fetch`, if one wants to use it in
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// an environment that is not the browser or node they have to setup a
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// global fetch polyfill.
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return null;
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} else {
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let isHTTP = true;
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if (Array.isArray(url)) {
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isHTTP = url.every(urlItem => isHTTPScheme(urlItem));
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} else {
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isHTTP = isHTTPScheme(url);
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}
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if (isHTTP) {
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return http(url, {onProgress});
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}
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}
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return null;
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};
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IORouterRegistry.registerSaveRouter(httpRouter);
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IORouterRegistry.registerLoadRouter(httpRouter);
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/**
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* Creates an IOHandler subtype that sends model artifacts to HTTP server.
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*
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* An HTTP request of the `multipart/form-data` mime type will be sent to the
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* `path` URL. The form data includes artifacts that represent the topology
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* and/or weights of the model. In the case of Keras-style `tf.Model`, two
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* blobs (files) exist in form-data:
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* - A JSON file consisting of `modelTopology` and `weightsManifest`.
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* - A binary weights file consisting of the concatenated weight values.
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* These files are in the same format as the one generated by
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* [tfjs_converter](https://js.tensorflow.org/tutorials/import-keras.html).
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*
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* The following code snippet exemplifies the client-side code that uses this
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* function:
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*
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* ```js
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* const model = tf.sequential();
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* model.add(
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* tf.layers.dense({units: 1, inputShape: [100], activation: 'sigmoid'}));
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*
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* const saveResult = await model.save(tf.io.http(
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* 'http://model-server:5000/upload', {requestInit: {method: 'PUT'}}));
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* console.log(saveResult);
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* ```
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*
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* If the default `POST` method is to be used, without any custom parameters
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* such as headers, you can simply pass an HTTP or HTTPS URL to `model.save`:
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*
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* ```js
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* const saveResult = await model.save('http://model-server:5000/upload');
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* ```
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*
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* The following GitHub Gist
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* https://gist.github.com/dsmilkov/1b6046fd6132d7408d5257b0976f7864
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* implements a server based on [flask](https://github.com/pallets/flask) that
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* can receive the request. Upon receiving the model artifacts via the requst,
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* this particular server reconsistutes instances of [Keras
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* Models](https://keras.io/models/model/) in memory.
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*
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*
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* @param path A URL path to the model.
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* Can be an absolute HTTP path (e.g.,
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* 'http://localhost:8000/model-upload)') or a relative path (e.g.,
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* './model-upload').
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* @param requestInit Request configurations to be used when sending
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* HTTP request to server using `fetch`. It can contain fields such as
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* `method`, `credentials`, `headers`, `mode`, etc. See
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* https://developer.mozilla.org/en-US/docs/Web/API/Request/Request
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* for more information. `requestInit` must not have a body, because the
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* body will be set by TensorFlow.js. File blobs representing the model
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* topology (filename: 'model.json') and the weights of the model (filename:
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* 'model.weights.bin') will be appended to the body. If `requestInit` has a
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* `body`, an Error will be thrown.
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* @param loadOptions Optional configuration for the loading. It includes the
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* following fields:
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* - weightPathPrefix Optional, this specifies the path prefix for weight
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* files, by default this is calculated from the path param.
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* - fetchFunc Optional, custom `fetch` function. E.g., in Node.js,
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* the `fetch` from node-fetch can be used here.
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* - onProgress Optional, progress callback function, fired periodically
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* before the load is completed.
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* @returns An instance of `IOHandler`.
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*/
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/**
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* @doc {
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* heading: 'Models',
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* subheading: 'Loading',
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* namespace: 'io',
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* ignoreCI: true
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* }
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*/
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export function http(path: string, loadOptions?: LoadOptions): IOHandler {
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return new HTTPRequest(path, loadOptions);
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}
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/**
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* Deprecated. Use `tf.io.http`.
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* @param path
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* @param loadOptions
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*/
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export function browserHTTPRequest(
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path: string, loadOptions?: LoadOptions): IOHandler {
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return http(path, loadOptions);
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}
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