@tensorflow/tfjs-core
Version:
Hardware-accelerated JavaScript library for machine intelligence
197 lines • 11.9 kB
JavaScript
;
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 = y[op[0] & 2 ? "return" : op[0] ? "throw" : "next"]) && !(t = t.call(y, op[1])).done) return t;
if (y = 0, t) op = [0, 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 });
var ops_1 = require("../ops/ops");
var util = require("../util");
var types_1 = require("./types");
function loadWeightsAsArrayBuffer(fetchURLs, requestOptions) {
return __awaiter(this, void 0, void 0, function () {
var requests, responses, buffers;
return __generator(this, function (_a) {
switch (_a.label) {
case 0:
requests = fetchURLs.map(function (fetchURL) { return fetch(fetchURL, requestOptions); });
return [4, Promise.all(requests)];
case 1:
responses = _a.sent();
return [4, Promise.all(responses.map(function (response) { return response.arrayBuffer(); }))];
case 2:
buffers = _a.sent();
return [2, buffers];
}
});
});
}
exports.loadWeightsAsArrayBuffer = loadWeightsAsArrayBuffer;
function loadWeights(manifest, filePathPrefix, weightNames, requestOptions) {
if (filePathPrefix === void 0) { filePathPrefix = ''; }
return __awaiter(this, void 0, void 0, function () {
var groupIndicesToFetchMap, groupWeightsToFetch, weightsFound, allManifestWeightNames, weightsNotFound, groupIndicesToFetch, fetchUrls, buffers, weightsTensorMap, bufferIndexOffset;
return __generator(this, function (_a) {
switch (_a.label) {
case 0:
groupIndicesToFetchMap = manifest.map(function () { return false; });
groupWeightsToFetch = {};
weightsFound = weightNames != null ? weightNames.map(function () { return false; }) : [];
allManifestWeightNames = [];
manifest.forEach(function (manifestGroupConfig, groupIndex) {
var groupOffset = 0;
manifestGroupConfig.weights.forEach(function (weightsEntry) {
var rawDtype = ('quantization' in weightsEntry) ?
weightsEntry.quantization.dtype :
weightsEntry.dtype;
var weightsBytes = types_1.DTYPE_VALUE_SIZE_MAP[rawDtype] *
util.sizeFromShape(weightsEntry.shape);
var enqueueWeightsForFetchingFn = function () {
groupIndicesToFetchMap[groupIndex] = true;
if (groupWeightsToFetch[groupIndex] == null) {
groupWeightsToFetch[groupIndex] = [];
}
groupWeightsToFetch[groupIndex].push({
manifestEntry: weightsEntry,
groupOffset: groupOffset,
sizeBytes: weightsBytes
});
};
if (weightNames != null) {
weightNames.forEach(function (weightName, weightIndex) {
if (weightName === weightsEntry.name) {
enqueueWeightsForFetchingFn();
weightsFound[weightIndex] = true;
}
});
}
else {
enqueueWeightsForFetchingFn();
}
allManifestWeightNames.push(weightsEntry.name);
groupOffset += weightsBytes;
});
});
if (!weightsFound.every(function (found) { return found; })) {
weightsNotFound = weightNames.filter(function (weight, i) { return !weightsFound[i]; });
throw new Error("Could not find weights in manifest with names: " +
(weightsNotFound.join(', ') + ". \n") +
"Manifest JSON has weights with names: " +
(allManifestWeightNames.join(', ') + "."));
}
groupIndicesToFetch = groupIndicesToFetchMap.reduce(function (accumulator, shouldFetch, i) {
if (shouldFetch) {
accumulator.push(i);
}
return accumulator;
}, []);
fetchUrls = [];
groupIndicesToFetch.forEach(function (i) {
manifest[i].paths.forEach(function (filepath) {
var fetchUrl = filePathPrefix +
(!filePathPrefix.endsWith('/') ? '/' : '') + filepath;
fetchUrls.push(fetchUrl);
});
});
return [4, loadWeightsAsArrayBuffer(fetchUrls, requestOptions)];
case 1:
buffers = _a.sent();
weightsTensorMap = {};
bufferIndexOffset = 0;
groupIndicesToFetch.forEach(function (i) {
var numBuffers = manifest[i].paths.length;
var groupBytes = 0;
for (var i_1 = 0; i_1 < numBuffers; i_1++) {
groupBytes += buffers[bufferIndexOffset + i_1].byteLength;
}
var groupBuffer = new ArrayBuffer(groupBytes);
var groupByteBuffer = new Uint8Array(groupBuffer);
var groupBufferOffset = 0;
for (var i_2 = 0; i_2 < numBuffers; i_2++) {
var buffer = new Uint8Array(buffers[bufferIndexOffset + i_2]);
groupByteBuffer.set(buffer, groupBufferOffset);
groupBufferOffset += buffer.byteLength;
}
var weightsEntries = groupWeightsToFetch[i];
weightsEntries.forEach(function (weightsEntry) {
var byteBuffer = groupBuffer.slice(weightsEntry.groupOffset, weightsEntry.groupOffset + weightsEntry.sizeBytes);
var typedArray;
var dtype = weightsEntry.manifestEntry.dtype;
if ('quantization' in weightsEntry.manifestEntry) {
var quantization_1 = weightsEntry.manifestEntry.quantization;
if (quantization_1.dtype !== 'uint8' && quantization_1.dtype !== 'uint16') {
throw new Error("Weight " + weightsEntry.manifestEntry.name + " has unknown " +
("quantization dtype " + quantization_1.dtype + "."));
}
var quantizedArray = (quantization_1.dtype === 'uint8') ?
new Uint8Array(byteBuffer) :
new Uint16Array(byteBuffer);
if (dtype === 'float32') {
typedArray = Float32Array.from(quantizedArray, function (v) { return v * quantization_1.scale + quantization_1.min; });
}
else if (dtype === 'int32') {
typedArray = Int32Array.from(quantizedArray, function (v) { return Math.round(v * quantization_1.scale + quantization_1.min); });
}
else {
throw new Error("Weight " + weightsEntry.manifestEntry.name + " has a dtype not " +
("supported by quantization: " + dtype));
}
}
else {
if (dtype === 'float32') {
typedArray = new Float32Array(byteBuffer);
}
else if (dtype === 'int32') {
typedArray = new Int32Array(byteBuffer);
}
else {
throw new Error("Weight " + weightsEntry.manifestEntry.name + " has unknown dtype " +
(dtype + "."));
}
}
var weightName = weightsEntry.manifestEntry.name;
if (weightsTensorMap[weightName] != null) {
throw new Error("Duplicate weight with name " + weightName + ". " +
"Please make sure weights names are unique in the manifest JSON.");
}
weightsTensorMap[weightName] = ops_1.tensor(typedArray, weightsEntry.manifestEntry.shape, weightsEntry.manifestEntry.dtype);
});
bufferIndexOffset += numBuffers;
});
return [2, weightsTensorMap];
}
});
});
}
exports.loadWeights = loadWeights;
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