mirror of
https://github.com/newnius/YAO-optimizer.git
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update
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2
.idea/workspace.xml
generated
2
.idea/workspace.xml
generated
@@ -248,7 +248,7 @@
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<component name="PropertiesComponent">
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<property name="WebServerToolWindowFactoryState" value="false" />
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<property name="aspect.path.notification.shown" value="true" />
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<property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588411500458" />
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<property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588411617480" />
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<property name="go.gopath.indexing.explicitly.defined" value="true" />
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<property name="nodejs_interpreter_path.stuck_in_default_project" value="undefined stuck path" />
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<property name="nodejs_npm_path_reset_for_default_project" value="true" />
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15
serve.py
15
serve.py
@@ -137,19 +137,19 @@ def predict(job, seq):
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}
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df = pd.read_csv('./data/' + job + '.csv', usecols=['seq', 'value'])
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df = df.tail(models[job]['batch_size'] * 2 - 1)
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df = df.tail(int(models[job]['batch_size']) * 2 - 1)
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df = df.append(data, ignore_index=True)
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batch_size = int(models[job]['batch_size'])
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# transform data to be stationary
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raw_values = df.values
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diff_values = difference(raw_values, 1)[models[job]['batch_size']:]
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diff_values = difference(raw_values, 1)[batch_size:]
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# transform data to be supervised learning
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lag = 4
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supervised = timeseries_to_supervised(diff_values, lag)
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supervised_values = supervised.values
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batch_size = models[job]['batch_size']
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test = supervised_values
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test = test.reshape(test.shape[0], test.shape[1])
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@@ -192,9 +192,12 @@ class MyHandler(BaseHTTPRequestHandler):
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try:
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job = query.get('job')[0]
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seq = query.get('seq')[0]
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predict(job, int(seq))
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msg = {'code': 0, 'error': ""}
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pred, success = predict(job, int(seq))
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if not success:
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msg = {'code': 2, 'error': "Job " + job + " not exist"}
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except Exception as e:
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msg = {'code': 1, 'error': str(e)}
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