@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
"use strict";
/**
* @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.
* =============================================================================
*/
var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
return new (P || (P = Promise))(function (resolve, reject) {
function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
function step(result) { result.done ? resolve(result.value) : new P(function (resolve) { resolve(result.value); }).then(fulfilled, rejected); }
step((generator = generator.apply(thisArg, _arguments || [])).next());
});
};
var __generator = (this && this.__generator) || function (thisArg, body) {
var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;
return g = { next: verb(0), "throw": verb(1), "return": verb(2) }, typeof Symbol === "function" && (g[Symbol.iterator] = function() { return this; }), g;
function verb(n) { return function (v) { return step([n, v]); }; }
function step(op) {
if (f) throw new TypeError("Generator is already executing.");
while (_) try {
if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
if (y = 0, t) op = [op[0] & 2, t.value];
switch (op[0]) {
case 0: case 1: t = op; break;
case 4: _.label++; return { value: op[1], done: false };
case 5: _.label++; y = op[1]; op = [0]; continue;
case 7: op = _.ops.pop(); _.trys.pop(); continue;
default:
if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }
if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }
if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }
if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }
if (t[2]) _.ops.pop();
_.trys.pop(); continue;
}
op = body.call(thisArg, _);
} catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }
if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };
}
};
Object.defineProperty(exports, "__esModule", { value: true });
/**
* IOHandler implementations based on HTTP requests in the web browser.
*
* Uses [`fetch`](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API).
*/
var environment_1 = require("../environment");
var util_1 = require("../util");
var io_utils_1 = require("./io_utils");
var router_registry_1 = require("./router_registry");
var weights_loader_1 = require("./weights_loader");
var OCTET_STREAM_MIME_TYPE = 'application/octet-stream';
var JSON_TYPE = 'application/json';
var HTTPRequest = /** @class */ (function () {
function HTTPRequest(path, loadOptions) {
this.DEFAULT_METHOD = 'POST';
if (loadOptions == null) {
loadOptions = {};
}
this.weightPathPrefix = loadOptions.weightPathPrefix;
this.onProgress = loadOptions.onProgress;
if (loadOptions.fetchFunc != null) {
util_1.assert(typeof loadOptions.fetchFunc === 'function', function () { return 'Must pass a function that matches the signature of ' +
'`fetch` (see ' +
'https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)'; });
this.fetch = loadOptions.fetchFunc;
}
else {
this.fetch = environment_1.env().platform.fetch;
}
util_1.assert(path != null && path.length > 0, function () { return 'URL path for http must not be null, undefined or ' +
'empty.'; });
if (Array.isArray(path)) {
util_1.assert(path.length === 2, function () { return 'URL paths for http must have a length of 2, ' +
("(actual length is " + path.length + ")."); });
}
this.path = path;
if (loadOptions.requestInit != null &&
loadOptions.requestInit.body != null) {
throw new Error('requestInit is expected to have no pre-existing body, but has one.');
}
this.requestInit = loadOptions.requestInit || {};
}
HTTPRequest.prototype.save = function (modelArtifacts) {
return __awaiter(this, void 0, void 0, function () {
var init, weightsManifest, modelTopologyAndWeightManifest, response;
return __generator(this, function (_a) {
switch (_a.label) {
case 0:
if (modelArtifacts.modelTopology instanceof ArrayBuffer) {
throw new Error('BrowserHTTPRequest.save() does not support saving model topology ' +
'in binary formats yet.');
}
init = Object.assign({ method: this.DEFAULT_METHOD }, this.requestInit);
init.body = new FormData();
weightsManifest = [{
paths: ['./model.weights.bin'],
weights: modelArtifacts.weightSpecs,
}];
modelTopologyAndWeightManifest = {
modelTopology: modelArtifacts.modelTopology,
format: modelArtifacts.format,
generatedBy: modelArtifacts.generatedBy,
convertedBy: modelArtifacts.convertedBy,
userDefinedMetadata: modelArtifacts.userDefinedMetadata,
weightsManifest: weightsManifest
};
init.body.append('model.json', new Blob([JSON.stringify(modelTopologyAndWeightManifest)], { type: JSON_TYPE }), 'model.json');
if (modelArtifacts.weightData != null) {
init.body.append('model.weights.bin', new Blob([modelArtifacts.weightData], { type: OCTET_STREAM_MIME_TYPE }), 'model.weights.bin');
}
return [4 /*yield*/, this.fetch(this.path, init)];
case 1:
response = _a.sent();
if (response.ok) {
return [2 /*return*/, {
modelArtifactsInfo: io_utils_1.getModelArtifactsInfoForJSON(modelArtifacts),
responses: [response],
}];
}
else {
throw new Error("BrowserHTTPRequest.save() failed due to HTTP response status " +
(response.status + "."));
}
return [2 /*return*/];
}
});
});
};
/**
* 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).
*/
HTTPRequest.prototype.load = function () {
return __awaiter(this, void 0, void 0, function () {
var modelConfigRequest, modelConfig, e_1, message, modelTopology, weightsManifest, generatedBy, convertedBy, format, userDefinedMetadata, weightSpecs, weightData, results;
return __generator(this, function (_a) {
switch (_a.label) {
case 0: return [4 /*yield*/, this.fetch(this.path, this.requestInit)];
case 1:
modelConfigRequest = _a.sent();
if (!modelConfigRequest.ok) {
throw new Error("Request to " + this.path + " failed with status code " +
(modelConfigRequest.status + ". Please verify this URL points to ") +
"the model JSON of the model to load.");
}
_a.label = 2;
case 2:
_a.trys.push([2, 4, , 5]);
return [4 /*yield*/, modelConfigRequest.json()];
case 3:
modelConfig = _a.sent();
return [3 /*break*/, 5];
case 4:
e_1 = _a.sent();
message = "Failed to parse model JSON of response from " + this.path + ".";
// TODO(nsthorat): Remove this after some time when we're comfortable that
// .pb files are mostly gone.
if (this.path.endsWith('.pb')) {
message += ' Your path contains a .pb file extension. ' +
'Support for .pb models have been removed in TensorFlow.js 1.0 ' +
'in favor of .json models. You can re-convert your Python ' +
'TensorFlow model using the TensorFlow.js 1.0 conversion scripts ' +
'or you can convert your.pb models with the \'pb2json\'' +
'NPM script in the tensorflow/tfjs-converter repository.';
}
else {
message += ' Please make sure the server is serving valid ' +
'JSON for this request.';
}
throw new Error(message);
case 5:
modelTopology = modelConfig.modelTopology;
weightsManifest = modelConfig.weightsManifest;
generatedBy = modelConfig.generatedBy;
convertedBy = modelConfig.convertedBy;
format = modelConfig.format;
userDefinedMetadata = modelConfig.userDefinedMetadata;
// We do not allow both modelTopology and weightsManifest to be missing.
if (modelTopology == null && weightsManifest == null) {
throw new Error("The JSON from HTTP path " + this.path + " contains neither model " +
"topology or manifest for weights.");
}
if (!(weightsManifest != null)) return [3 /*break*/, 7];
return [4 /*yield*/, this.loadWeights(weightsManifest)];
case 6:
results = _a.sent();
weightSpecs = results[0], weightData = results[1];
_a.label = 7;
case 7: return [2 /*return*/, {
modelTopology: modelTopology,
weightSpecs: weightSpecs,
weightData: weightData,
userDefinedMetadata: userDefinedMetadata,
generatedBy: generatedBy,
convertedBy: convertedBy,
format: format
}];
}
});
});
};
HTTPRequest.prototype.loadWeights = function (weightsManifest) {
return __awaiter(this, void 0, void 0, function () {
var weightPath, _a, prefix, suffix, pathPrefix, weightSpecs, _i, weightsManifest_1, entry, fetchURLs, buffers;
return __generator(this, function (_b) {
switch (_b.label) {
case 0:
weightPath = Array.isArray(this.path) ? this.path[1] : this.path;
_a = parseUrl(weightPath), prefix = _a[0], suffix = _a[1];
pathPrefix = this.weightPathPrefix || prefix;
weightSpecs = [];
for (_i = 0, weightsManifest_1 = weightsManifest; _i < weightsManifest_1.length; _i++) {
entry = weightsManifest_1[_i];
weightSpecs.push.apply(weightSpecs, entry.weights);
}
fetchURLs = [];
weightsManifest.forEach(function (weightsGroup) {
weightsGroup.paths.forEach(function (path) {
fetchURLs.push(pathPrefix + path + suffix);
});
});
return [4 /*yield*/, weights_loader_1.loadWeightsAsArrayBuffer(fetchURLs, {
requestInit: this.requestInit,
fetchFunc: this.fetch,
onProgress: this.onProgress
})];
case 1:
buffers = _b.sent();
return [2 /*return*/, [weightSpecs, io_utils_1.concatenateArrayBuffers(buffers)]];
}
});
});
};
HTTPRequest.URL_SCHEME_REGEX = /^https?:\/\//;
return HTTPRequest;
}());
exports.HTTPRequest = HTTPRequest;
/**
* 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.
*/
function parseUrl(url) {
var lastSlash = url.lastIndexOf('/');
var lastSearchParam = url.lastIndexOf('?');
var prefix = url.substring(0, lastSlash);
var suffix = lastSearchParam > lastSlash ? url.substring(lastSearchParam) : '';
return [prefix + '/', suffix];
}
exports.parseUrl = parseUrl;
function isHTTPScheme(url) {
return url.match(HTTPRequest.URL_SCHEME_REGEX) != null;
}
exports.isHTTPScheme = isHTTPScheme;
exports.httpRouter = function (url, onProgress) {
if (typeof fetch === 'undefined') {
// `http` uses `fetch` or `node-fetch`, if one wants to use it in
// an environment that is not the browser or node they have to setup a
// global fetch polyfill.
return null;
}
else {
var isHTTP = true;
if (Array.isArray(url)) {
isHTTP = url.every(function (urlItem) { return isHTTPScheme(urlItem); });
}
else {
isHTTP = isHTTPScheme(url);
}
if (isHTTP) {
return http(url, { onProgress: onProgress });
}
}
return null;
};
router_registry_1.IORouterRegistry.registerSaveRouter(exports.httpRouter);
router_registry_1.IORouterRegistry.registerLoadRouter(exports.httpRouter);
/**
* 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 requst,
* this particular server reconsistutes 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
* }
*/
function http(path, loadOptions) {
return new HTTPRequest(path, loadOptions);
}
exports.http = http;
/**
* Deprecated. Use `tf.io.http`.
* @param path
* @param loadOptions
*/
function browserHTTPRequest(path, loadOptions) {
return http(path, loadOptions);
}
exports.browserHTTPRequest = browserHTTPRequest;
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