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68 lines
2.8 KiB
Python
Executable File
68 lines
2.8 KiB
Python
Executable File
# Copyright 2014-2018 ARM Limited
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#
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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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import re
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from wa import ApkUiautoWorkload
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from wa.framework.exception import WorkloadError
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class Aitutu(ApkUiautoWorkload):
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name = 'aitutu'
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package_names = ['com.antutu.aibenchmark']
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regex_matches = [re.compile(r'Overall Score ([\d.]+)'),
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re.compile(r'Image Total Score ([\d.]+) ([\w]+) ([\w]+)'),
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re.compile(r'Image Speed Score ([\d.]+) ([\w]+) ([\w]+)'),
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re.compile(r'Image Accuracy Score ([\d.]+) ([\w]+) ([\w]+)'),
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re.compile(r'Object Total Score ([\d.]+) ([\w]+) ([\w]+)'),
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re.compile(r'Object Speed Score ([\d.]+) ([\w]+) ([\w]+)'),
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re.compile(r'Object Accuracy Score ([\d.]+) ([\w]+) ([\w]+)')]
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description = '''
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Executes Aitutu Image Speed/Accuracy and Object Speed/Accuracy tests
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The Aitutu workflow carries out the following tasks.
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1. Open Aitutu application
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2. Download the resources for the test
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3. Execute the tests
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Known working APK version: 1.0.3
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'''
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def __init__(self, target, **kwargs):
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super(Aitutu, self).__init__(target, **kwargs)
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self.gui.timeout = 1200000
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def update_output(self, context):
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super(Aitutu, self).update_output(context)
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expected_results = len(self.regex_matches)
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logcat_file = context.get_artifact_path('logcat')
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with open(logcat_file) as fh:
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for line in fh:
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for regex in self.regex_matches:
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match = regex.search(line)
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if match:
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classifiers = {}
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result = match.group(1)
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if (len(match.groups())) > 1:
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entry = regex.pattern.rsplit(None, 3)[0]
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classifiers = {'model': match.group(3)}
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else:
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entry = regex.pattern.rsplit(None, 1)[0]
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context.add_metric(entry, result, '', lower_is_better=False, classifiers=classifiers)
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expected_results -= 1
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if expected_results > 0:
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msg = "The Aitutu workload has failed. Expected {} scores, Detected {} scores."
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raise WorkloadError(msg.format(len(self.regex_matches), expected_results))
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