diff --git a/.idea/workspace.xml b/.idea/workspace.xml
index 63a1c03..19a2eea 100644
--- a/.idea/workspace.xml
+++ b/.idea/workspace.xml
@@ -1,9 +1,7 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
   <component name="ChangeListManager">
-    <list default="true" id="0aedafd8-e57e-462a-beda-65af0b91f3df" name="Default Changelist" comment="">
-      <change beforePath="$PROJECT_DIR$/serve.py" beforeDir="false" afterPath="$PROJECT_DIR$/serve.py" afterDir="false" />
-    </list>
+    <list default="true" id="0aedafd8-e57e-462a-beda-65af0b91f3df" name="Default Changelist" comment="" />
     <ignored path="$PROJECT_DIR$/out/" />
     <option name="EXCLUDED_CONVERTED_TO_IGNORED" value="true" />
     <option name="SHOW_DIALOG" value="false" />
@@ -15,8 +13,9 @@
     <session id="570274097">
       <usages-collector id="statistics.lifecycle.project">
         <counts>
+          <entry key="project.open.time.1" value="1" />
           <entry key="project.open.time.3" value="1" />
-          <entry key="project.opened" value="1" />
+          <entry key="project.opened" value="2" />
         </counts>
       </usages-collector>
       <usages-collector id="statistics.file.extensions.open">
@@ -24,43 +23,49 @@
           <entry key="Dockerfile" value="1" />
           <entry key="csv" value="2" />
           <entry key="iml" value="1" />
-          <entry key="md" value="1" />
+          <entry key="md" value="2" />
           <entry key="png" value="7" />
-          <entry key="py" value="6" />
+          <entry key="py" value="7" />
+          <entry key="sh" value="2" />
           <entry key="txt" value="2" />
         </counts>
       </usages-collector>
       <usages-collector id="statistics.file.types.open">
         <counts>
+          <entry key="Bash" value="2" />
           <entry key="Dockerfile" value="1" />
           <entry key="IDEA_MODULE" value="1" />
           <entry key="Image" value="7" />
-          <entry key="Markdown" value="1" />
+          <entry key="Markdown" value="2" />
           <entry key="PLAIN_TEXT" value="4" />
-          <entry key="Python" value="6" />
+          <entry key="Python" value="7" />
         </counts>
       </usages-collector>
       <usages-collector id="statistics.file.extensions.edit">
         <counts>
-          <entry key="Dockerfile" value="16" />
-          <entry key="py" value="1357" />
+          <entry key="Dockerfile" value="81" />
+          <entry key="md" value="104" />
+          <entry key="py" value="2825" />
+          <entry key="sh" value="5" />
         </counts>
       </usages-collector>
       <usages-collector id="statistics.file.types.edit">
         <counts>
-          <entry key="Dockerfile" value="16" />
-          <entry key="Python" value="1357" />
+          <entry key="Bash" value="5" />
+          <entry key="Dockerfile" value="81" />
+          <entry key="Markdown" value="104" />
+          <entry key="Python" value="2825" />
         </counts>
       </usages-collector>
     </session>
   </component>
   <component name="FileEditorManager">
-    <leaf>
+    <leaf SIDE_TABS_SIZE_LIMIT_KEY="300">
       <file pinned="false" current-in-tab="false">
         <entry file="file://$PROJECT_DIR$/main.py">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="2160">
-              <caret line="144" column="4" selection-start-line="144" selection-start-column="4" selection-end-line="144" selection-end-column="30" />
+            <state relative-caret-position="176">
+              <caret line="199" column="32" lean-forward="true" selection-start-line="199" selection-start-column="32" selection-end-line="199" selection-end-column="32" />
               <folding>
                 <element signature="e#0#19#0" expanded="true" />
               </folding>
@@ -69,41 +74,56 @@
         </entry>
       </file>
       <file pinned="false" current-in-tab="false">
-        <entry file="file://$PROJECT_DIR$/data/stock_data.csv">
+        <entry file="file://$PROJECT_DIR$/serve.py">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="60">
-              <caret line="4" column="37" selection-start-line="4" selection-start-column="37" selection-end-line="4" selection-end-column="37" />
+            <state relative-caret-position="-1056">
+              <caret line="43" column="16" lean-forward="true" selection-start-line="43" selection-start-column="16" selection-end-line="43" selection-end-column="16" />
+              <folding>
+                <element signature="e#18#46#0" expanded="true" />
+                <marker date="1588357497851" expanded="true" signature="5576:5578" ph="..." />
+              </folding>
             </state>
           </provider>
         </entry>
       </file>
       <file pinned="false" current-in-tab="true">
-        <entry file="file://$PROJECT_DIR$/serve.py">
+        <entry file="file://$PROJECT_DIR$/train.py">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="260">
-              <caret line="53" column="28" selection-start-line="53" selection-start-column="28" selection-end-line="53" selection-end-column="28" />
+            <state relative-caret-position="1580">
+              <caret line="110" column="61" lean-forward="true" selection-start-line="110" selection-start-column="61" selection-end-line="110" selection-end-column="62" />
               <folding>
-                <element signature="e#18#46#0" expanded="true" />
-                <marker date="1588180249558" expanded="true" signature="5697:5971" ph="..." />
+                <element signature="e#0#28#0" expanded="true" />
               </folding>
             </state>
           </provider>
         </entry>
       </file>
+      <file pinned="false" current-in-tab="false">
+        <entry file="file://$PROJECT_DIR$/README.md">
+          <provider selected="true" editor-type-id="split-provider[text-editor;markdown-preview-editor]">
+            <state split_layout="SPLIT">
+              <first_editor relative-caret-position="105">
+                <caret line="7" column="6" selection-start-line="7" selection-start-column="6" selection-end-line="7" selection-end-column="6" />
+              </first_editor>
+              <second_editor />
+            </state>
+          </provider>
+        </entry>
+      </file>
       <file pinned="false" current-in-tab="false">
         <entry file="file://$PROJECT_DIR$/Dockerfile">
           <provider selected="true" editor-type-id="text-editor">
             <state relative-caret-position="180">
-              <caret line="12" column="24" selection-start-line="12" selection-start-column="24" selection-end-line="12" selection-end-column="24" />
+              <caret line="12" column="58" selection-start-line="12" selection-start-column="58" selection-end-line="12" selection-end-column="58" />
             </state>
           </provider>
         </entry>
       </file>
       <file pinned="false" current-in-tab="false">
-        <entry file="file://$PROJECT_DIR$/requirements.txt">
+        <entry file="file://$PROJECT_DIR$/bootstrap.sh">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="120">
-              <caret line="8" lean-forward="true" selection-start-line="8" selection-end-line="8" />
+            <state relative-caret-position="30">
+              <caret line="2" column="22" lean-forward="true" selection-start-line="2" selection-start-column="22" selection-end-line="2" selection-end-column="22" />
             </state>
           </provider>
         </entry>
@@ -111,8 +131,8 @@
       <file pinned="false" current-in-tab="false">
         <entry file="file://$PROJECT_DIR$/model_tensorflow.py">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="358">
-              <caret line="59" column="45" selection-start-line="59" selection-start-column="45" selection-end-line="59" selection-end-column="45" />
+            <state relative-caret-position="157">
+              <caret line="50" column="56" selection-start-line="50" selection-start-column="56" selection-end-line="50" selection-end-column="56" />
               <folding>
                 <element signature="e#0#23#0" expanded="true" />
               </folding>
@@ -134,6 +154,16 @@
       <find>lstm</find>
       <find>used</find>
       <find>mean</find>
+      <find>std</find>
+      <find>usecol</find>
+      <find>valid_data_rate</find>
+      <find>batch_size</find>
+      <find>predict</find>
+      <find>train_num</find>
+      <find>label_in_feature_columns</find>
+      <find>epoch</find>
+      <find>timeseries_to_supervised</find>
+      <find>batch_index</find>
     </findStrings>
   </component>
   <component name="Git.Settings">
@@ -145,10 +175,13 @@
         <option value="$PROJECT_DIR$/test.py" />
         <option value="$PROJECT_DIR$/model/model_tensorflow.py" />
         <option value="$PROJECT_DIR$/requirements.txt" />
-        <option value="$PROJECT_DIR$/main.py" />
-        <option value="$PROJECT_DIR$/Dockerfile" />
+        <option value="$PROJECT_DIR$/bootstrap.sh" />
+        <option value="$PROJECT_DIR$/README.md" />
         <option value="$PROJECT_DIR$/model_tensorflow.py" />
+        <option value="$PROJECT_DIR$/Dockerfile" />
         <option value="$PROJECT_DIR$/serve.py" />
+        <option value="$PROJECT_DIR$/main.py" />
+        <option value="$PROJECT_DIR$/train.py" />
       </list>
     </option>
   </component>
@@ -167,8 +200,6 @@
       <foldersAlwaysOnTop value="true" />
     </navigator>
     <panes>
-      <pane id="AndroidView" />
-      <pane id="PackagesPane" />
       <pane id="ProjectPane">
         <subPane>
           <expand>
@@ -185,13 +216,15 @@
           <select />
         </subPane>
       </pane>
+      <pane id="AndroidView" />
+      <pane id="PackagesPane" />
       <pane id="Scope" />
     </panes>
   </component>
   <component name="PropertiesComponent">
     <property name="WebServerToolWindowFactoryState" value="false" />
     <property name="aspect.path.notification.shown" value="true" />
-    <property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588180252829" />
+    <property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588395483884" />
     <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_npm_path_reset_for_default_project" value="true" />
@@ -201,13 +234,13 @@
     <property name="settings.editor.selected.configurable" value="http.proxy" />
   </component>
   <component name="RecentsManager">
-    <key name="CopyFile.RECENT_KEYS">
-      <recent name="$PROJECT_DIR$" />
-    </key>
     <key name="MoveFile.RECENT_KEYS">
       <recent name="$PROJECT_DIR$" />
       <recent name="$PROJECT_DIR$/model" />
     </key>
+    <key name="CopyFile.RECENT_KEYS">
+      <recent name="$PROJECT_DIR$" />
+    </key>
   </component>
   <component name="RunDashboard">
     <option name="ruleStates">
@@ -232,21 +265,23 @@
       <option name="presentableId" value="Default" />
       <updated>1588152877746</updated>
       <workItem from="1588152880522" duration="16973000" />
+      <workItem from="1588319878551" duration="26780000" />
     </task>
     <servers />
   </component>
   <component name="TimeTrackingManager">
-    <option name="totallyTimeSpent" value="16973000" />
+    <option name="totallyTimeSpent" value="43753000" />
   </component>
   <component name="ToolWindowManager">
     <frame x="0" y="0" width="1280" height="800" extended-state="0" />
+    <editor active="true" />
     <layout>
       <window_info id="Designer" order="0" />
       <window_info id="UI Designer" order="1" />
       <window_info id="Capture Tool" order="2" />
       <window_info id="Favorites" order="3" side_tool="true" />
       <window_info id="Image Layers" order="4" />
-      <window_info content_ui="combo" id="Project" order="5" sideWeight="0.49898168" visible="true" weight="0.24959612" />
+      <window_info content_ui="combo" id="Project" order="5" sideWeight="0.49898168" visible="true" weight="0.2536349" />
       <window_info id="Structure" order="6" sideWeight="0.50101835" side_tool="true" weight="0.24959612" />
       <window_info anchor="bottom" id="Version Control" order="0" />
       <window_info active="true" anchor="bottom" id="Terminal" order="1" visible="true" weight="0.32739726" />
@@ -282,59 +317,25 @@
     <entry file="file://$PROJECT_DIR$/yao-optimizer.iml">
       <provider selected="true" editor-type-id="text-editor" />
     </entry>
-    <entry file="file://$PROJECT_DIR$/test.py">
-      <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="150">
-          <caret line="52" column="30" selection-start-line="52" selection-start-column="30" selection-end-line="52" selection-end-column="30" />
-          <folding>
-            <element signature="e#0#19#0" expanded="true" />
-          </folding>
-        </state>
-      </provider>
-    </entry>
-    <entry file="file://$PROJECT_DIR$/figure/continue_predict_high_with_pytorch.png">
-      <provider selected="true" editor-type-id="images" />
-    </entry>
-    <entry file="file://$PROJECT_DIR$/figure/continue_predict_low_with_pytorch.png">
-      <provider selected="true" editor-type-id="images" />
-    </entry>
-    <entry file="file://$PROJECT_DIR$/figure/predict_high_with_keras.png">
-      <provider selected="true" editor-type-id="images" />
-    </entry>
-    <entry file="file://$PROJECT_DIR$/figure/predict_low_with_tensorflow.png">
-      <provider selected="true" editor-type-id="images" />
-    </entry>
-    <entry file="file://$PROJECT_DIR$/figure/predict_low_with_keras.png">
-      <provider selected="true" editor-type-id="images" />
-    </entry>
-    <entry file="file://$PROJECT_DIR$/figure/predict_high_with_tensorflow.png">
-      <provider selected="true" editor-type-id="images" />
-    </entry>
-    <entry file="file://$PROJECT_DIR$/figure/predict_high_with_pytorch.png">
-      <provider selected="true" editor-type-id="images" />
-    </entry>
-    <entry file="file://$PROJECT_DIR$/Readme.md">
-      <provider selected="true" editor-type-id="split-provider[text-editor;markdown-preview-editor]">
-        <state split_layout="SPLIT">
-          <first_editor />
-          <second_editor />
-        </state>
-      </provider>
-    </entry>
+    <entry file="file://$PROJECT_DIR$/test.py" />
+    <entry file="file://$PROJECT_DIR$/figure/continue_predict_high_with_pytorch.png" />
+    <entry file="file://$PROJECT_DIR$/figure/continue_predict_low_with_pytorch.png" />
+    <entry file="file://$PROJECT_DIR$/figure/predict_high_with_keras.png" />
+    <entry file="file://$PROJECT_DIR$/figure/predict_low_with_tensorflow.png" />
+    <entry file="file://$PROJECT_DIR$/figure/predict_low_with_keras.png" />
+    <entry file="file://$PROJECT_DIR$/figure/predict_high_with_tensorflow.png" />
+    <entry file="file://$PROJECT_DIR$/figure/predict_high_with_pytorch.png" />
     <entry file="file://$PROJECT_DIR$/requirements.txt">
       <provider selected="true" editor-type-id="text-editor">
         <state relative-caret-position="120">
-          <caret line="8" lean-forward="true" selection-start-line="8" selection-end-line="8" />
+          <caret line="8" selection-start-line="8" selection-end-line="8" />
         </state>
       </provider>
     </entry>
-    <entry file="file://$PROJECT_DIR$/main.py">
+    <entry file="file://$PROJECT_DIR$/bootstrap.sh">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="2160">
-          <caret line="144" column="4" selection-start-line="144" selection-start-column="4" selection-end-line="144" selection-end-column="30" />
-          <folding>
-            <element signature="e#0#19#0" expanded="true" />
-          </folding>
+        <state relative-caret-position="30">
+          <caret line="2" column="22" lean-forward="true" selection-start-line="2" selection-start-column="22" selection-end-line="2" selection-end-column="22" />
         </state>
       </provider>
     </entry>
@@ -348,27 +349,57 @@
     <entry file="file://$PROJECT_DIR$/Dockerfile">
       <provider selected="true" editor-type-id="text-editor">
         <state relative-caret-position="180">
-          <caret line="12" column="24" selection-start-line="12" selection-start-column="24" selection-end-line="12" selection-end-column="24" />
+          <caret line="12" column="58" selection-start-line="12" selection-start-column="58" selection-end-line="12" selection-end-column="58" />
+        </state>
+      </provider>
+    </entry>
+    <entry file="file://$PROJECT_DIR$/README.md">
+      <provider selected="true" editor-type-id="split-provider[text-editor;markdown-preview-editor]">
+        <state split_layout="SPLIT">
+          <first_editor relative-caret-position="105">
+            <caret line="7" column="6" selection-start-line="7" selection-start-column="6" selection-end-line="7" selection-end-column="6" />
+          </first_editor>
+          <second_editor />
+        </state>
+      </provider>
+    </entry>
+    <entry file="file://$PROJECT_DIR$/serve.py">
+      <provider selected="true" editor-type-id="text-editor">
+        <state relative-caret-position="-1056">
+          <caret line="43" column="16" lean-forward="true" selection-start-line="43" selection-start-column="16" selection-end-line="43" selection-end-column="16" />
+          <folding>
+            <element signature="e#18#46#0" expanded="true" />
+            <marker date="1588357497851" expanded="true" signature="5576:5578" ph="..." />
+          </folding>
         </state>
       </provider>
     </entry>
     <entry file="file://$PROJECT_DIR$/model_tensorflow.py">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="358">
-          <caret line="59" column="45" selection-start-line="59" selection-start-column="45" selection-end-line="59" selection-end-column="45" />
+        <state relative-caret-position="157">
+          <caret line="50" column="56" selection-start-line="50" selection-start-column="56" selection-end-line="50" selection-end-column="56" />
           <folding>
             <element signature="e#0#23#0" expanded="true" />
           </folding>
         </state>
       </provider>
     </entry>
-    <entry file="file://$PROJECT_DIR$/serve.py">
+    <entry file="file://$PROJECT_DIR$/main.py">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="260">
-          <caret line="53" column="28" selection-start-line="53" selection-start-column="28" selection-end-line="53" selection-end-column="28" />
+        <state relative-caret-position="176">
+          <caret line="199" column="32" lean-forward="true" selection-start-line="199" selection-start-column="32" selection-end-line="199" selection-end-column="32" />
           <folding>
-            <element signature="e#18#46#0" expanded="true" />
-            <marker date="1588180249558" expanded="true" signature="5697:5971" ph="..." />
+            <element signature="e#0#19#0" expanded="true" />
+          </folding>
+        </state>
+      </provider>
+    </entry>
+    <entry file="file://$PROJECT_DIR$/train.py">
+      <provider selected="true" editor-type-id="text-editor">
+        <state relative-caret-position="1580">
+          <caret line="110" column="61" lean-forward="true" selection-start-line="110" selection-start-column="61" selection-end-line="110" selection-end-column="62" />
+          <folding>
+            <element signature="e#0#28#0" expanded="true" />
           </folding>
         </state>
       </provider>
diff --git a/Dockerfile b/Dockerfile
index 88d1875..d9a5e0b 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -10,11 +10,13 @@ RUN apt update && \
 	apt install -y git vim httpie && \
 	rm -rf /var/lib/apt/lists/*
 
-RUN pip3 install pandas sklearn tensorflow-gpu==1.14
+RUN pip3 install pandas sklearn tensorflow-gpu==1.14 keras
 
 ADD bootstrap.sh /etc/bootstrap.sh
 
-ADD agent.py /root/agent.py
+RUN mkdir /root/data/
+ADD serve.py /root/serve.py
+ADD model_tensorflow.py /root/model_tensorflow.py
 
 WORKDIR /root
 
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..be165d8
--- /dev/null
+++ b/README.md
@@ -0,0 +1,11 @@
+
+
+## Feed
+
+/feed?job=1&model=2&time=3&utilGPU=4&utilCPU=5&pre=1&main=2&post=3
+
+## train
+/train
+
+## predict
+/predict?job=1&model=2&time=3&utilGPU=4&utilCPU=5
\ No newline at end of file
diff --git a/bootstrap.sh b/bootstrap.sh
new file mode 100755
index 0000000..6552432
--- /dev/null
+++ b/bootstrap.sh
@@ -0,0 +1,3 @@
+#!/usr/bin/env bash
+
+python3 /root/serve.py
\ No newline at end of file
diff --git a/serve.py b/serve.py
index c40bbb5..3a50801 100644
--- a/serve.py
+++ b/serve.py
@@ -14,8 +14,8 @@ import csv
 
 
 class Config:
-	feature_columns = list(range(0, 6))
-	label_columns = [3, 4, 5]
+	feature_columns = list(range(0, 2))
+	label_columns = [1]
 	feature_and_label_columns = feature_columns + label_columns
 	label_in_feature_columns = (lambda x, y: [x.index(i) for i in y])(feature_columns, label_columns)
 
@@ -34,7 +34,8 @@ class Config:
 	add_train = False
 	shuffle_train_data = True
 
-	train_data_rate = 0.95
+	# train_data_rate = 0.95 #comment yqy
+	train_data_rate = 1  # add yqy
 	valid_data_rate = 0.15
 
 	batch_size = 64
@@ -50,10 +51,10 @@ class Config:
 		batch_size = 1
 		continue_flag = "continue_"
 
-	train_data_path = "./data.csv"
-	test_data_path = "./test.csv"
+	train_data_path = "./data/data.csv"
 	model_save_path = "./checkpoint/"
 	figure_save_path = "./figure/"
+
 	do_figure_save = False
 	if not os.path.exists(model_save_path):
 		os.mkdir(model_save_path)
@@ -74,17 +75,14 @@ class Data:
 		self.train_num = int(self.data_num * self.config.train_data_rate)
 
 		self.mean = np.mean(self.data, axis=0)
-
-		self.std = np.std(self.data, axis=0)
+		self.std = np.std(self.data, axis=0) + 0.0001
 		self.norm_data = (self.data - self.mean) / self.std
 
 		self.start_num_in_test = 0
 
 	def read_data(self):
-		init_data = pd.read_csv(
-			self.config.train_data_path,
-			usecols=self.config.feature_and_label_columns
-		)
+		init_data = pd.read_csv(self.config.train_data_path,
+		                        usecols=self.config.feature_and_label_columns)
 		return init_data.values, init_data.columns.tolist()
 
 	def get_train_and_valid_data(self):
@@ -112,22 +110,6 @@ class Data:
 		return train_x, valid_x, train_y, valid_y
 
 	def get_test_data(self, return_label_data=False):
-		init_data = pd.read_csv(
-			self.config.test_data_path,
-			usecols=self.config.feature_and_label_columns
-		)
-		norm_data = (init_data - self.mean) / self.std
-		feature_data = norm_data[:]
-		time_step_size = feature_data.shape[0] // self.config.time_step
-
-		test_x = [feature_data[0 + i * self.config.time_step: 0 + (
-				i + 1) * self.config.time_step]
-		          for i in range(time_step_size)]
-		if return_label_data:
-			label_data = norm_data[0:, self.config.label_in_feature_columns]
-			return np.array(test_x), label_data
-		return np.array(test_x)
-
 		feature_data = self.norm_data[self.train_num:]
 		self.start_num_in_test = feature_data.shape[0] % self.config.time_step
 		time_step_size = feature_data.shape[0] // self.config.time_step
@@ -140,31 +122,50 @@ class Data:
 			return np.array(test_x), label_data
 		return np.array(test_x)
 
+	# add yqy
+	def get_test_data_yqy(self, test_data_yqy=None):
+		if test_data_yqy is None:
+			test_data_yqy = []
+		# test_data_yqy=test_data_yqy[1:21]
+		feature_data = (test_data_yqy - self.mean) / self.std
+		test_x = [feature_data]
+		return np.array(test_x)
 
-def draw(config, origin_data, predict_norm_data):
-	label_norm_data = origin_data.norm_data[origin_data.train_num + origin_data.start_num_in_test:,
-	                  config.label_in_feature_columns]
+
+# add end
+
+
+def draw_yqy(config2, origin_data, predict_norm_data, mean_yqy, std_yqy):
+	label_norm_data = (origin_data - mean_yqy) / std_yqy
 	assert label_norm_data.shape[0] == predict_norm_data.shape[
 		0], "The element number in origin and predicted data is different"
 
-	label_name = [origin_data.data_column_name[i] for i in config.label_in_feature_columns]
-	label_column_num = len(config.label_columns)
+	print("dsa")
+	# label_norm_data=label_norm_data[:,1]
+	label_name = 'high'
+	label_column_num = 3
 
-	loss = np.mean((label_norm_data[config.predict_day:] - predict_norm_data[:-config.predict_day]) ** 2, axis=0)
+	loss = \
+		np.mean((label_norm_data[config.predict_day:, 1:2] - predict_norm_data[:-config.predict_day]) ** 2, axis=0)
 	print("The mean squared error of stock {} is ".format(label_name), loss)
 
-	label_X = range(origin_data.data_num - origin_data.train_num - origin_data.start_num_in_test)
-	predict_X = [x + config.predict_day for x in label_X]
+	# label_X = range(origin_data.data_num - origin_data.train_num - origin_data.start_num_in_test)
+	# predict_X = [x + config.predict_day for x in label_X]
 
-	label_data = label_norm_data * origin_data.std[config.label_in_feature_columns] + \
-	             origin_data.mean[config.label_in_feature_columns]
-
-	predict_data = predict_norm_data * origin_data.std[config.label_in_feature_columns] + \
-	               origin_data.mean[config.label_in_feature_columns]
+	print("2")
 
+	print(label_norm_data[:, 1:2])
+	label_data = label_norm_data[:, 1:2] * std_yqy[1:2] + mean_yqy[1:2]
 	print(label_data)
+
+	print(predict_norm_data)
+	predict_data = predict_norm_data * std_yqy[config.label_in_feature_columns] + mean_yqy[
+		config.label_in_feature_columns]
 	print(predict_data)
 
+	print(label_data[:, -1])
+	print(predict_data[:, -1])
+
 
 PORT_NUMBER = 8080
 lock = Lock()
@@ -179,6 +180,11 @@ def train_models():
 	train_X, valid_X, train_Y, valid_Y = data_gainer.get_train_and_valid_data()
 
 	print(train_X, valid_X, train_Y, valid_Y)
+	print(train_X.shape[0])
+	if train_X.shape[0] < 500:
+		config.batch_size = 32
+	if train_X.shape[0] < 200:
+		config.batch_size = 16
 
 	train(config, train_X, train_Y, valid_X, valid_Y)
 
@@ -199,15 +205,39 @@ class MyHandler(BaseHTTPRequestHandler):
 
 		elif req.path == "/predict":
 			try:
-				job = query.get('job')[0]
-				gpu_model = query.get('gpu_model')[0]
-				time = query.get('time')[0]
+				data = {
+					'job': query.get('job')[0],
+					'model': query.get('model')[0],
+					'time': query.get('time')[0],
+					'utilGPU': query.get('utilGPU')[0],
+					'utilCPU': query.get('utilCPU')[0],
+					'pre': 0,
+					'main': 0,
+					'post': 0
+				}
+
+				data = {
+					'seq': query.get('job')[0],
+					'value': query.get('model')[0],
+				}
+
+				with open(config.train_data_path, 'r') as f:
+					df = pd.read_csv(config.train_data_path, usecols=['seq', 'value'])
+					df = df.tail(config.time_step - 1)
+					df = df.append(data, ignore_index=True)
+					df.to_csv('./data/test_data.csv', index=False)
+
+				np.random.seed(config.random_seed)
 				data_gainer = Data(config)
-				test_X, test_Y = data_gainer.get_test_data(return_label_data=True)
-				print(test_X, test_Y)
+				test_data_yqy = pd.read_csv("./data/test_data.csv", usecols=list(range(0, 2)))
+				test_data_values = test_data_yqy.values[:]
+				test_X = data_gainer.get_test_data_yqy(test_data_values)
 				pred_result = predict(config, test_X)
-				print(pred_result)
-				draw(config, data_gainer, pred_result)
+
+				mean = Data(config).mean
+				std = Data(config).std
+				draw_yqy(config, test_data_values, pred_result, mean, std)
+
 				msg = {'code': 1, 'error': "container not exist"}
 			except Exception as e:
 				msg = {'code': 2, 'error': str(e)}
@@ -221,15 +251,22 @@ class MyHandler(BaseHTTPRequestHandler):
 				job = query.get('job')[0]
 				model = query.get('model')[0]
 				time = query.get('time')[0]
+				utilGPU = query.get('utilGPU')[0]
+				utilCPU = query.get('utilCPU')[0]
 				pre = query.get('pre')[0]
 				main = query.get('main')[0]
 				post = query.get('post')[0]
+
+				seq = query.get('seq')[0]
+				value = query.get('value')[0]
+
 				with open(config.train_data_path, 'a+', newline='') as csvfile:
 					spamwriter = csv.writer(
 						csvfile, delimiter=',',
 						quotechar='|', quoting=csv.QUOTE_MINIMAL
 					)
-					spamwriter.writerow([job, model, time, pre, main, post])
+					# spamwriter.writerow([job, model, time, utilGPU, utilCPU, pre, main, post])
+					spamwriter.writerow([seq, value])
 				msg = {'code': 1, 'error': "container not exist"}
 			except Exception as e:
 				msg = {'code': 2, 'error': str(e)}
@@ -293,7 +330,8 @@ if __name__ == '__main__':
 				csvfile, delimiter=',',
 				quotechar='|', quoting=csv.QUOTE_MINIMAL
 			)
-			spamwriter.writerow(["Job", "Model", "Time", "Pre", "Main", "Post"])
+			#spamwriter.writerow(["job", "model", "time", "utilGPU", "utilCPU", "pre", "main", "post"])
+			spamwriter.writerow(["seq", "value"])
 
 		# Wait forever for incoming http requests
 		server.serve_forever()
diff --git a/train.py b/train.py
new file mode 100644
index 0000000..9d7d35e
--- /dev/null
+++ b/train.py
@@ -0,0 +1,157 @@
+from pandas import DataFrame
+from pandas import Series
+from pandas import concat
+from pandas import read_csv
+from sklearn.metrics import mean_squared_error
+from sklearn.preprocessing import MinMaxScaler
+from keras.models import Sequential
+from keras.layers import Dense
+from keras.layers import LSTM
+from math import sqrt
+import numpy
+
+
+# frame a sequence as a supervised learning problem
+def timeseries_to_supervised(data, lag=1):
+	df = DataFrame(data)
+	columns = [df.shift(i) for i in range(1, lag + 1)]
+	columns.append(df)
+	df = concat(columns, axis=1)
+	df = df.drop(0)
+	return df
+
+
+# create a differenced series
+def difference(dataset, interval=1):
+	diff = list()
+	for i in range(interval, len(dataset)):
+		value = dataset[i] - dataset[i - interval]
+		diff.append(value)
+	return Series(diff)
+
+
+# invert differenced value
+def inverse_difference(history, yhat, interval=1):
+	return yhat + history[-interval]
+
+
+# scale train and test data to [-1, 1]
+def scale(train, test):
+	# fit scaler
+	scaler = MinMaxScaler(feature_range=(-1, 1))
+	scaler = scaler.fit(train)
+	# transform train
+	train = train.reshape(train.shape[0], train.shape[1])
+	train_scaled = scaler.transform(train)
+	# transform test
+	test = test.reshape(test.shape[0], test.shape[1])
+	test_scaled = scaler.transform(test)
+	return scaler, train_scaled, test_scaled
+
+
+# inverse scaling for a forecasted value
+def invert_scale(scaler, X, yhat):
+	new_row = [x for x in X] + [yhat]
+	array = numpy.array(new_row)
+	array = array.reshape(1, len(array))
+	inverted = scaler.inverse_transform(array)
+	return inverted[0, -1]
+
+
+# fit an LSTM network to training data
+def fit_lstm(train, batch_size2, nb_epoch, neurons):
+	print(train)
+	X, y = train[:, 0:-1], train[:, -1]
+	X = X.reshape(X.shape[0], 1, X.shape[1])
+	print(X, y)
+	model = Sequential()
+	model.add(LSTM(neurons, batch_input_shape=(batch_size2, X.shape[1], X.shape[2]), stateful=True))
+	model.add(Dense(1))
+	model.compile(loss='mean_squared_error', optimizer='adam')
+	for i in range(nb_epoch):
+		print("Epoch {}/{}".format(i, nb_epoch))
+		model.fit(X, y, epochs=1, batch_size=batch_size2, verbose=0, shuffle=False)
+		#loss, accuracy = model.evaluate(X, y)
+		#print(loss, accuracy)
+		model.reset_states()
+	return model
+
+
+# make a one-step forecast
+def forecast_lstm(model, batch_size, X):
+	X = X.reshape(1, 1, len(X))
+	yhat = model.predict(X, batch_size=batch_size)
+	return yhat[0, 0]
+
+
+# run a repeated experiment
+def experiment(repeats, series, seed):
+	# transform data to be stationary
+	raw_values = series.values
+	diff_values = difference(raw_values, 1)
+	# transform data to be supervised learning
+	lag2 = 4
+	supervised = timeseries_to_supervised(diff_values, lag2)
+	supervised_values = supervised.values
+
+	test_data_num = 32
+	# split data into train and test-sets
+	train, test = supervised_values[0:-test_data_num], supervised_values[-test_data_num:]
+	# transform the scale of the data
+	print(test)
+	scaler, train_scaled, test_scaled = scale(train, test)
+	print(test_scaled)
+	# run experiment
+	error_scores = list()
+	for r in range(repeats):
+		# fit the model
+		batch_size = 32
+		t1 = train.shape[0] % batch_size
+		t2 = test.shape[0] % batch_size
+
+		train_trimmed = train_scaled[t1:, :]
+		lstm_model = fit_lstm(train_trimmed, batch_size, 30, 4)
+		# forecast the entire training dataset to build up state for forecasting
+		print(train_trimmed)
+		print(train_trimmed[:, 0])
+		print(train_trimmed[:, :-1])
+		# if seed:
+		#	train_reshaped = train_trimmed[:, :-1].reshape(len(train_trimmed), 1, lag2)
+		#	lstm_model.predict(train_reshaped, batch_size=batch_size)
+		# forecast test dataset
+		test_reshaped = test_scaled[:, 0:-1]
+		test_reshaped = test_reshaped.reshape(len(test_reshaped), 1, lag2)
+		output = lstm_model.predict(test_reshaped, batch_size=batch_size)
+		predictions = list()
+		for i in range(len(output)):
+			yhat = output[i, 0]
+			X = test_scaled[i, 0:-1]
+			# invert scaling
+			yhat = invert_scale(scaler, X, yhat)
+			# invert differencing
+			yhat = inverse_difference(raw_values, yhat, len(test_scaled) + 1 - i)
+			# store forecast
+			predictions.append(yhat)
+		# report performance
+		rmse = sqrt(mean_squared_error(raw_values[-test_data_num:], predictions))
+		print(predictions, raw_values[-test_data_num:])
+		print('%d) Test RMSE: %.3f' % (r + 1, rmse))
+		error_scores.append(rmse)
+	return error_scores
+
+
+# load dataset
+series = read_csv('data.csv', header=0, index_col=0, squeeze=True)
+# experiment
+repeats = 1
+results = DataFrame()
+# with seeding
+with_seed = experiment(repeats, series, True)
+results['with-seed'] = with_seed
+# without seeding
+without_seed = experiment(repeats, series, False)
+results['without-seed'] = without_seed
+# summarize results
+print(results.describe())
+# save boxplot
+results.boxplot()