@tensorflow/tfjs-core
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Hardware-accelerated JavaScript library for machine intelligence
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JavaScript
;
/**
* @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 };
}
};
var _this = this;
Object.defineProperty(exports, "__esModule", { value: true });
var tf = require("../index");
var jasmine_util_1 = require("../jasmine_util");
var io_utils_1 = require("./io_utils");
var local_storage_1 = require("./local_storage");
jasmine_util_1.describeWithFlags('LocalStorage', jasmine_util_1.BROWSER_ENVS, function () {
// Test data.
var modelTopology1 = {
'class_name': 'Sequential',
'keras_version': '2.1.4',
'config': [{
'class_name': 'Dense',
'config': {
'kernel_initializer': {
'class_name': 'VarianceScaling',
'config': {
'distribution': 'uniform',
'scale': 1.0,
'seed': null,
'mode': 'fan_avg'
}
},
'name': 'dense',
'kernel_constraint': null,
'bias_regularizer': null,
'bias_constraint': null,
'dtype': 'float32',
'activation': 'linear',
'trainable': true,
'kernel_regularizer': null,
'bias_initializer': { 'class_name': 'Zeros', 'config': {} },
'units': 1,
'batch_input_shape': [null, 3],
'use_bias': true,
'activity_regularizer': null
}
}],
'backend': 'tensorflow'
};
var weightSpecs1 = [
{
name: 'dense/kernel',
shape: [3, 1],
dtype: 'float32',
},
{
name: 'dense/bias',
shape: [1],
dtype: 'float32',
}
];
var weightData1 = new ArrayBuffer(16);
var artifacts1 = {
modelTopology: modelTopology1,
weightSpecs: weightSpecs1,
weightData: weightData1,
format: 'layers-model',
generatedBy: 'TensorFlow.js v0.0.0',
convertedBy: '1.13.1',
userDefinedMetadata: {}
};
var artifactsV0 = {
modelTopology: modelTopology1,
weightSpecs: weightSpecs1,
weightData: weightData1
};
function findOverflowingByteSize() {
var LS = window.localStorage;
var probeKey = "tfjs_test_probe_values_" + new Date().getTime() + "_" + Math.random();
var minKilobytes = 200;
var stepKilobytes = 200;
var maxKilobytes = 40000;
for (var kilobytes = minKilobytes; kilobytes < maxKilobytes; kilobytes += stepKilobytes) {
var bytes = kilobytes * 1024;
var data = new ArrayBuffer(bytes);
try {
var encoded = io_utils_1.arrayBufferToBase64String(data);
LS.setItem(probeKey, encoded);
}
catch (err) {
return bytes;
}
LS.removeItem(probeKey);
}
throw new Error("Unable to determined overflowing byte size up to " + maxKilobytes + " kB.");
}
beforeEach(function () {
local_storage_1.purgeLocalStorageArtifacts();
});
afterEach(function () {
local_storage_1.purgeLocalStorageArtifacts();
});
it('Save artifacts succeeds', function (done) {
var testStartDate = new Date();
var handler = tf.io.getSaveHandlers('localstorage://foo/FooModel')[0];
handler.save(artifacts1)
.then(function (saveResult) {
expect(saveResult.modelArtifactsInfo.dateSaved.getTime())
.toBeGreaterThanOrEqual(testStartDate.getTime());
// Note: The following two assertions work only because there is no
// non-ASCII characters in `modelTopology1` and `weightSpecs1`.
expect(saveResult.modelArtifactsInfo.modelTopologyBytes)
.toEqual(JSON.stringify(modelTopology1).length);
expect(saveResult.modelArtifactsInfo.weightSpecsBytes)
.toEqual(JSON.stringify(weightSpecs1).length);
expect(saveResult.modelArtifactsInfo.weightDataBytes).toEqual(16);
// Check the content of the saved items in local storage.
var LS = window.localStorage;
var info = JSON.parse(LS.getItem('tensorflowjs_models/foo/FooModel/info'));
expect(Date.parse(info.dateSaved))
.toEqual(saveResult.modelArtifactsInfo.dateSaved.getTime());
expect(info.modelTopologyBytes)
.toEqual(saveResult.modelArtifactsInfo.modelTopologyBytes);
expect(info.weightSpecsBytes)
.toEqual(saveResult.modelArtifactsInfo.weightSpecsBytes);
expect(info.weightDataBytes)
.toEqual(saveResult.modelArtifactsInfo.weightDataBytes);
var topologyString = LS.getItem('tensorflowjs_models/foo/FooModel/model_topology');
expect(JSON.stringify(modelTopology1)).toEqual(topologyString);
var weightSpecsString = LS.getItem('tensorflowjs_models/foo/FooModel/weight_specs');
expect(JSON.stringify(weightSpecs1)).toEqual(weightSpecsString);
var weightDataBase64String = LS.getItem('tensorflowjs_models/foo/FooModel/weight_data');
expect(io_utils_1.base64StringToArrayBuffer(weightDataBase64String))
.toEqual(weightData1);
done();
})
.catch(function (err) {
console.error(err.stack);
});
});
it('Save-load round trip succeeds', function () { return __awaiter(_this, void 0, void 0, function () {
var handler1, handler2, loaded;
return __generator(this, function (_a) {
switch (_a.label) {
case 0:
handler1 = tf.io.getSaveHandlers('localstorage://FooModel')[0];
return [4 /*yield*/, handler1.save(artifacts1)];
case 1:
_a.sent();
handler2 = tf.io.getLoadHandlers('localstorage://FooModel')[0];
return [4 /*yield*/, handler2.load()];
case 2:
loaded = _a.sent();
expect(loaded.modelTopology).toEqual(modelTopology1);
expect(loaded.weightSpecs).toEqual(weightSpecs1);
expect(loaded.weightData).toEqual(weightData1);
expect(loaded.format).toEqual('layers-model');
expect(loaded.generatedBy).toEqual('TensorFlow.js v0.0.0');
expect(loaded.convertedBy).toEqual('1.13.1');
expect(loaded.userDefinedMetadata).toEqual({});
return [2 /*return*/];
}
});
}); });
it('Save-load round trip succeeds: v0 format', function () { return __awaiter(_this, void 0, void 0, function () {
var handler1, handler2, loaded;
return __generator(this, function (_a) {
switch (_a.label) {
case 0:
handler1 = tf.io.getSaveHandlers('localstorage://FooModel')[0];
return [4 /*yield*/, handler1.save(artifactsV0)];
case 1:
_a.sent();
handler2 = tf.io.getLoadHandlers('localstorage://FooModel')[0];
return [4 /*yield*/, handler2.load()];
case 2:
loaded = _a.sent();
expect(loaded.modelTopology).toEqual(modelTopology1);
expect(loaded.weightSpecs).toEqual(weightSpecs1);
expect(loaded.weightData).toEqual(weightData1);
expect(loaded.format).toBeUndefined();
expect(loaded.generatedBy).toBeUndefined();
expect(loaded.convertedBy).toBeUndefined();
expect(loaded.userDefinedMetadata).toBeUndefined();
return [2 /*return*/];
}
});
}); });
it('Loading nonexistent model fails.', function (done) {
var handler = tf.io.getSaveHandlers('localstorage://NonexistentModel')[0];
handler.load()
.then(function (artifacts) {
fail('Loading nonexistent model succeeded unexpectedly.');
})
.catch(function (err) {
expect(err.message)
.toEqual('In local storage, there is no model with name ' +
'\'NonexistentModel\'');
done();
});
});
it('Loading model with missing topology fails.', function (done) {
var handler1 = tf.io.getSaveHandlers('localstorage://FooModel')[0];
handler1.save(artifacts1)
.then(function (saveResult) {
// Manually remove the topology item from local storage.
window.localStorage.removeItem('tensorflowjs_models/FooModel/model_topology');
var handler2 = tf.io.getLoadHandlers('localstorage://FooModel')[0];
handler2.load()
.then(function (artifacts) {
fail('Loading of model with missing topology succeeded ' +
'unexpectedly.');
})
.catch(function (err) {
expect(err.message)
.toEqual('In local storage, the topology of model ' +
'\'FooModel\' is missing.');
done();
});
})
.catch(function (err) {
console.error(err.stack);
});
});
it('Loading model with missing weight specs fails.', function (done) {
var handler1 = tf.io.getSaveHandlers('localstorage://FooModel')[0];
handler1.save(artifacts1)
.then(function (saveResult) {
// Manually remove the weight specs item from local storage.
window.localStorage.removeItem('tensorflowjs_models/FooModel/weight_specs');
var handler2 = tf.io.getLoadHandlers('localstorage://FooModel')[0];
handler2.load()
.then(function (artifacts) {
fail('Loading of model with missing weight specs succeeded ' +
'unexpectedly.');
})
.catch(function (err) {
expect(err.message)
.toEqual('In local storage, the weight specs of model ' +
'\'FooModel\' are missing.');
done();
});
})
.catch(function (err) {
console.error(err.stack);
});
});
it('Loading model with missing weight data fails.', function (done) {
var handler1 = tf.io.getSaveHandlers('localstorage://FooModel')[0];
handler1.save(artifacts1)
.then(function (saveResult) {
// Manually remove the weight data item from local storage.
window.localStorage.removeItem('tensorflowjs_models/FooModel/weight_data');
var handler2 = tf.io.getLoadHandlers('localstorage://FooModel')[0];
handler2.load()
.then(function (artifacts) {
fail('Loading of model with missing weight data succeeded ' +
'unexpectedly.');
})
.catch(function (err) {
expect(err.message)
.toEqual('In local storage, the binary weight values of model ' +
'\'FooModel\' are missing.');
done();
});
})
.catch(function (err) {
console.error(err.stack);
});
});
it('Data size too large leads to error thrown', function (done) {
var overflowByteSize = findOverflowingByteSize();
var overflowArtifacts = {
modelTopology: modelTopology1,
weightSpecs: weightSpecs1,
weightData: new ArrayBuffer(overflowByteSize),
};
var handler1 = tf.io.getSaveHandlers('localstorage://FooModel')[0];
handler1.save(overflowArtifacts)
.then(function (saveResult) {
fail('Saving of model of overflowing-size weight data succeeded ' +
'unexpectedly.');
})
.catch(function (err) {
expect(err.message
.indexOf('Failed to save model \'FooModel\' to local storage'))
.toEqual(0);
done();
});
});
it('Null, undefined or empty modelPath throws Error', function () {
expect(function () { return local_storage_1.browserLocalStorage(null); })
.toThrowError(/local storage, modelPath must not be null, undefined or empty/);
expect(function () { return local_storage_1.browserLocalStorage(undefined); })
.toThrowError(/local storage, modelPath must not be null, undefined or empty/);
expect(function () { return local_storage_1.browserLocalStorage(''); })
.toThrowError(/local storage, modelPath must not be null, undefined or empty./);
});
it('router', function () {
expect(local_storage_1.localStorageRouter('localstorage://bar') instanceof local_storage_1.BrowserLocalStorage)
.toEqual(true);
expect(local_storage_1.localStorageRouter('indexeddb://bar')).toBeNull();
expect(local_storage_1.localStorageRouter('qux')).toBeNull();
});
it('Manager: List models: 0 result', function (done) {
// Before any model is saved, listModels should return empty result.
new local_storage_1.BrowserLocalStorageManager()
.listModels()
.then(function (out) {
expect(out).toEqual({});
done();
})
.catch(function (err) { return done.fail(err.stack); });
});
it('Manager: List models: 1 result', function (done) {
var handler = tf.io.getSaveHandlers('localstorage://baz/QuxModel')[0];
handler.save(artifacts1)
.then(function (saveResult) {
// After successful saving, there should be one model.
new local_storage_1.BrowserLocalStorageManager()
.listModels()
.then(function (out) {
expect(Object.keys(out).length).toEqual(1);
expect(out['baz/QuxModel'].modelTopologyType)
.toEqual(saveResult.modelArtifactsInfo.modelTopologyType);
expect(out['baz/QuxModel'].modelTopologyBytes)
.toEqual(saveResult.modelArtifactsInfo.modelTopologyBytes);
expect(out['baz/QuxModel'].weightSpecsBytes)
.toEqual(saveResult.modelArtifactsInfo.weightSpecsBytes);
expect(out['baz/QuxModel'].weightDataBytes)
.toEqual(saveResult.modelArtifactsInfo.weightDataBytes);
done();
})
.catch(function (err) { return done.fail(err.stack); });
})
.catch(function (err) { return done.fail(err.stack); });
});
it('Manager: List models: 2 results', function (done) {
// First, save a model.
var handler1 = tf.io.getSaveHandlers('localstorage://QuxModel')[0];
handler1.save(artifacts1)
.then(function (saveResult1) {
// Then, save the model under another path.
var handler2 = tf.io.getSaveHandlers('localstorage://repeat/QuxModel')[0];
handler2.save(artifacts1)
.then(function (saveResult2) {
// After successful saving, there should be two models.
new local_storage_1.BrowserLocalStorageManager()
.listModels()
.then(function (out) {
expect(Object.keys(out).length).toEqual(2);
expect(out['QuxModel'].modelTopologyType)
.toEqual(saveResult1.modelArtifactsInfo.modelTopologyType);
expect(out['QuxModel'].modelTopologyBytes)
.toEqual(saveResult1.modelArtifactsInfo
.modelTopologyBytes);
expect(out['QuxModel'].weightSpecsBytes)
.toEqual(saveResult1.modelArtifactsInfo.weightSpecsBytes);
expect(out['QuxModel'].weightDataBytes)
.toEqual(saveResult1.modelArtifactsInfo.weightDataBytes);
expect(out['repeat/QuxModel'].modelTopologyType)
.toEqual(saveResult2.modelArtifactsInfo.modelTopologyType);
expect(out['repeat/QuxModel'].modelTopologyBytes)
.toEqual(saveResult2.modelArtifactsInfo
.modelTopologyBytes);
expect(out['repeat/QuxModel'].weightSpecsBytes)
.toEqual(saveResult2.modelArtifactsInfo.weightSpecsBytes);
expect(out['repeat/QuxModel'].weightDataBytes)
.toEqual(saveResult2.modelArtifactsInfo.weightDataBytes);
done();
})
.catch(function (err) { return done.fail(err.stack); });
})
.catch(function (err) { return done.fail(err.stack); });
})
.catch(function (err) { return done.fail(err.stack); });
});
it('Manager: Successful deleteModel', function (done) {
// First, save a model.
var handler1 = tf.io.getSaveHandlers('localstorage://QuxModel')[0];
handler1.save(artifacts1)
.then(function (saveResult1) {
// Then, save the model under another path.
var handler2 = tf.io.getSaveHandlers('localstorage://repeat/QuxModel')[0];
handler2.save(artifacts1)
.then(function (saveResult2) {
// After successful saving, delete the first save, and then
// `listModel` should give only one result.
var manager = new local_storage_1.BrowserLocalStorageManager();
manager.removeModel('QuxModel')
.then(function (deletedInfo) {
manager.listModels().then(function (out) {
expect(Object.keys(out)).toEqual(['repeat/QuxModel']);
});
done();
})
.catch(function (err) { return done.fail(err.stack); });
})
.catch(function (err) { return done.fail(err.stack); });
})
.catch(function (err) { return done.fail(err.stack); });
});
});
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