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bundle_resource_io_test.ts
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/**
* @license
* Copyright 2019 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.
* =============================================================================
*/
import './platform_react_native';
import * as tf from '@tensorflow/tfjs-core';
// tslint:disable-next-line: no-imports-from-dist
import {describeWithFlags} from '@tensorflow/tfjs-core/dist/jasmine_util';
import {bundleResourceIO} from './bundle_resource_io';
import * as tfjsRn from './platform_react_native';
import {RN_ENVS} from './test_env_registry';
describeWithFlags('BundleResourceIO', RN_ENVS, () => {
// Test data.
const 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'
};
const weightSpecs1: tf.io.WeightsManifestEntry[] = [
{
name: 'dense/kernel',
shape: [3, 1],
dtype: 'float32',
},
{
name: 'dense/bias',
shape: [1],
dtype: 'float32',
}
];
const weightData1 = new ArrayBuffer(16);
it('constructs an IOHandler', async () => {
const modelJson: tf.io.ModelJSON = {
modelTopology: modelTopology1,
weightsManifest: [{
paths: [],
weights: weightSpecs1,
}]
};
const resourceId = 1;
const handler = bundleResourceIO(modelJson, resourceId);
expect(typeof handler.load).toBe('function');
expect(typeof handler.save).toBe('function');
});
it('loads model artifacts', async () => {
const response = new Response(weightData1);
spyOn(tfjsRn, 'fetch').and.returnValue(Promise.resolve(response));
const modelJson: tf.io.ModelJSON = {
modelTopology: modelTopology1,
weightsManifest: [{
paths: [],
weights: weightSpecs1,
}]
};
const resourceId = 1;
const handler = bundleResourceIO(modelJson, resourceId);
const loaded = await handler.load();
expect(loaded.modelTopology).toEqual(modelTopology1);
expect(loaded.weightSpecs).toEqual(weightSpecs1);
expect(loaded.weightData).toEqual(weightData1);
});
it('errors on string modelJSON', async () => {
const response = new Response(weightData1);
spyOn(tf.env().platform, 'fetch')
.and.returnValue(Promise.resolve(response));
const modelJson = `{
modelTopology: modelTopology1,
weightsManifest: [{
paths: [],
weights: weightSpecs1,
}]
}`;
const resourceId = 1;
expect(
() => bundleResourceIO(
modelJson as unknown as tf.io.ModelJSON, resourceId))
.toThrow(new Error(
'modelJson must be a JavaScript object (and not a string).\n' +
'Have you wrapped yor asset path in a require() statment?'));
});
});