1
0
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 17:43:00 +08:00
parent 517b222124
commit 71149dc594
2 changed files with 4 additions and 2 deletions

2
.idea/workspace.xml generated
View File

@@ -248,7 +248,7 @@
<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="1588412333754" /> <property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588412501852" />
<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

@@ -93,6 +93,7 @@ def train_models(job):
# transform data to be supervised learning # transform data to be supervised learning
lag = 4 lag = 4
supervised = timeseries_to_supervised(diff_values, lag) supervised = timeseries_to_supervised(diff_values, lag)
print(supervised)
supervised_values = supervised.values supervised_values = supervised.values
batch_size = 32 batch_size = 32
@@ -127,7 +128,7 @@ def train_models(job):
def predict(job, seq): def predict(job, seq):
if job not in models: if job not in models or 'model' not in models[job]:
return -1, False return -1, False
# load dataset # load dataset
@@ -151,6 +152,7 @@ def predict(job, seq):
# transform data to be supervised learning # transform data to be supervised learning
lag = 4 lag = 4
supervised = timeseries_to_supervised(diff_values, lag) supervised = timeseries_to_supervised(diff_values, lag)
print(type(supervised))
print(supervised) print(supervised)
supervised_values = supervised.values[batch_size:] supervised_values = supervised.values[batch_size:]