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mirror of https://github.com/newnius/YAO-optimizer.git synced 2025-12-13 08:26:43 +00:00
This commit is contained in:
2020-05-02 09:52:48 +08:00
parent 3c580a33d3
commit edf61d117d
2 changed files with 2 additions and 2 deletions

2
.idea/workspace.xml generated
View File

@@ -224,7 +224,7 @@
<component name="PropertiesComponent"> <component name="PropertiesComponent">
<property name="WebServerToolWindowFactoryState" value="false" /> <property name="WebServerToolWindowFactoryState" value="false" />
<property name="aspect.path.notification.shown" value="true" /> <property name="aspect.path.notification.shown" value="true" />
<property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588384042640" /> <property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588384213991" />
<property name="go.gopath.indexing.explicitly.defined" value="true" /> <property name="go.gopath.indexing.explicitly.defined" value="true" />
<property name="nodejs_interpreter_path.stuck_in_default_project" value="undefined stuck path" /> <property name="nodejs_interpreter_path.stuck_in_default_project" value="undefined stuck path" />
<property name="nodejs_npm_path_reset_for_default_project" value="true" /> <property name="nodejs_npm_path_reset_for_default_project" value="true" />

View File

@@ -104,7 +104,7 @@ train, test = supervised_values[0:-12], supervised_values[-12:]
scaler, train_scaled, test_scaled = scale(train, test) scaler, train_scaled, test_scaled = scale(train, test)
# fit the model # fit the model
lstm_model = fit_lstm(train_scaled, 1, 300, 4) lstm_model = fit_lstm(train_scaled, 1, 30, 4)
# forecast the entire training dataset to build up state for forecasting # forecast the entire training dataset to build up state for forecasting
train_reshaped = train_scaled[:, 0].reshape(len(train_scaled), 1, 1) train_reshaped = train_scaled[:, 0].reshape(len(train_scaled), 1, 1)
lstm_model.predict(train_reshaped, batch_size=1) lstm_model.predict(train_reshaped, batch_size=1)