diff --git a/.idea/workspace.xml b/.idea/workspace.xml
index 553f693b..b3be5a92 100644
--- a/.idea/workspace.xml
+++ b/.idea/workspace.xml
@@ -2,9 +2,11 @@
 <project version="4">
   <component name="ChangeListManager">
     <list default="true" id="69f12537-6c3d-43b1-a62a-ad07d70a14cd" name="Default" comment="">
-      <change type="NEW" beforePath="" afterPath="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/FISM.py" />
-      <change type="MODIFICATION" beforePath="$PROJECT_DIR$/.gitignore" afterPath="$PROJECT_DIR$/.gitignore" />
       <change type="MODIFICATION" beforePath="$PROJECT_DIR$/.idea/workspace.xml" afterPath="$PROJECT_DIR$/.idea/workspace.xml" />
+      <change type="MODIFICATION" beforePath="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Batch_gen.py" afterPath="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Batch_gen.py" />
+      <change type="MODIFICATION" beforePath="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Evaluate.py" afterPath="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Evaluate.py" />
+      <change type="MODIFICATION" beforePath="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/FISM.py" afterPath="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/FISM.py" />
+      <change type="MODIFICATION" beforePath="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/NAIS.py" afterPath="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/NAIS.py" />
     </list>
     <option name="EXCLUDED_CONVERTED_TO_IGNORED" value="true" />
     <option name="TRACKING_ENABLED" value="true" />
@@ -35,7 +37,7 @@
     <SUITE FILE_PATH="coverage/tensorflow1_2$main__1_.coverage" NAME="main (1) Coverage Results" MODIFIED="1545377037092" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/RL/Basic-DisRL-Demo" />
     <SUITE FILE_PATH="coverage/tensorflow1_2$preprocess__1_.coverage" NAME="preprocess (1) Coverage Results" MODIFIED="1542602954609" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/recommendation/Basic-MKR-Demo" />
     <SUITE FILE_PATH="coverage/tensorflow1_2$kg_preprocess.coverage" NAME="kg_preprocess Coverage Results" MODIFIED="1541604856562" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/recommendation/Basic-DKN-Demo/kg" />
-    <SUITE FILE_PATH="coverage/tensorflow1_2$NAIS.coverage" NAME="NAIS Coverage Results" MODIFIED="1551431946415" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo" />
+    <SUITE FILE_PATH="coverage/tensorflow1_2$NAIS.coverage" NAME="NAIS Coverage Results" MODIFIED="1551434396342" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo" />
     <SUITE FILE_PATH="coverage/tensorflow1_2$plotResult.coverage" NAME="plotResult Coverage Results" MODIFIED="1529723400750" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/recommendation/Basic-MLR-Demo" />
     <SUITE FILE_PATH="coverage/tensorflow1_2$news_preprocess.coverage" NAME="news_preprocess Coverage Results" MODIFIED="1541602017949" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/recommendation/Basic-DKN-Demo/news" />
     <SUITE FILE_PATH="coverage/tensorflow1_2$data.coverage" NAME="data Coverage Results" MODIFIED="1529689500332" SOURCE_PROVIDER="com.intellij.coverage.DefaultCoverageFileProvider" RUNNER="coverage.py" COVERAGE_BY_TEST_ENABLED="true" COVERAGE_TRACING_ENABLED="false" WORKING_DIRECTORY="$PROJECT_DIR$/recommendation/Basic-MLR-Demo" />
@@ -74,8 +76,8 @@
       <file leaf-file-name="NAIS.py" pinned="false" current-in-tab="false">
         <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/NAIS.py">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="172">
-              <caret line="182" column="43" lean-forward="false" selection-start-line="182" selection-start-column="43" selection-end-line="182" selection-end-column="43" />
+            <state relative-caret-position="169">
+              <caret line="260" column="22" lean-forward="false" selection-start-line="260" selection-start-column="17" selection-end-line="260" selection-end-column="22" />
               <folding>
                 <element signature="e#0#23#0" expanded="true" />
               </folding>
@@ -86,19 +88,17 @@
       <file leaf-file-name="Batch_gen.py" pinned="false" current-in-tab="false">
         <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Batch_gen.py">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="192">
-              <caret line="109" column="54" lean-forward="false" selection-start-line="109" selection-start-column="54" selection-end-line="109" selection-end-column="54" />
-              <folding>
-                <element signature="e#0#22#0" expanded="true" />
-              </folding>
+            <state relative-caret-position="209">
+              <caret line="160" column="18" lean-forward="false" selection-start-line="160" selection-start-column="13" selection-end-line="160" selection-end-column="18" />
+              <folding />
             </state>
           </provider>
         </entry>
       </file>
-      <file leaf-file-name=".gitignore" pinned="false" current-in-tab="true">
+      <file leaf-file-name=".gitignore" pinned="false" current-in-tab="false">
         <entry file="file://$PROJECT_DIR$/.gitignore">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="569">
+            <state relative-caret-position="634">
               <caret line="53" column="4" lean-forward="false" selection-start-line="53" selection-start-column="4" selection-end-line="53" selection-end-column="4" />
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@@ -108,37 +108,47 @@
       <file leaf-file-name="Evaluate.py" pinned="false" current-in-tab="false">
         <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Evaluate.py">
           <provider selected="true" editor-type-id="text-editor">
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-              <caret line="68" column="19" lean-forward="false" selection-start-line="68" selection-start-column="19" selection-end-line="68" selection-end-column="19" />
+            <state relative-caret-position="49">
+              <caret line="60" column="72" lean-forward="false" selection-start-line="60" selection-start-column="72" selection-end-line="60" selection-end-column="72" />
               <folding />
             </state>
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-      <file leaf-file-name="FISM.py" pinned="false" current-in-tab="false">
-        <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/FISM.py">
+      <file leaf-file-name="Dataset.py" pinned="false" current-in-tab="false">
+        <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Dataset.py">
           <provider selected="true" editor-type-id="text-editor">
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-              <caret line="180" column="112" lean-forward="false" selection-start-line="180" selection-start-column="112" selection-end-line="180" selection-end-column="112" />
+            <state relative-caret-position="15">
+              <caret line="13" column="63" lean-forward="false" selection-start-line="13" selection-start-column="63" selection-end-line="13" selection-end-column="63" />
               <folding>
-                <element signature="e#0#38#0" expanded="true" />
+                <element signature="e#0#25#0" expanded="true" />
               </folding>
             </state>
           </provider>
         </entry>
       </file>
-      <file leaf-file-name="Dataset.py" pinned="false" current-in-tab="false">
-        <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Dataset.py">
+      <file leaf-file-name="FISM.py" pinned="false" current-in-tab="true">
+        <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/FISM.py">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="195">
-              <caret line="13" column="63" lean-forward="false" selection-start-line="13" selection-start-column="63" selection-end-line="13" selection-end-column="63" />
+            <state relative-caret-position="139">
+              <caret line="158" column="0" lean-forward="true" selection-start-line="158" selection-start-column="0" selection-end-line="158" selection-end-column="0" />
               <folding>
-                <element signature="e#0#25#0" expanded="true" />
+                <element signature="e#0#38#0" expanded="true" />
               </folding>
             </state>
           </provider>
         </entry>
       </file>
+      <file leaf-file-name="ops.py" pinned="false" current-in-tab="false">
+        <entry file="file://$USER_HOME$/Anaconda/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/ops.py">
+          <provider selected="true" editor-type-id="text-editor">
+            <state relative-caret-position="209">
+              <caret line="1469" column="0" lean-forward="false" selection-start-line="1469" selection-start-column="0" selection-end-line="1469" selection-end-column="0" />
+              <folding />
+            </state>
+          </provider>
+        </entry>
+      </file>
     </leaf>
   </component>
   <component name="FileTemplateManagerImpl">
@@ -165,6 +175,8 @@
       <find>self.tfd</find>
       <find>positional_encoding</find>
       <find>self.num_idx</find>
+      <find>already load the evaluate model</find>
+      <find>range</find>
     </findStrings>
     <dirStrings>
       <dir>$PROJECT_DIR$/recommendation/Basic-NAIS-Demo</dir>
@@ -223,11 +235,11 @@
         <option value="$PROJECT_DIR$/recommendation/Basic-DMF-Model/main.py" />
         <option value="$PROJECT_DIR$/recommendation/Basic-DMF-Model/dataset.py" />
         <option value="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Dataset.py" />
+        <option value="$PROJECT_DIR$/.gitignore" />
+        <option value="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Batch_gen.py" />
         <option value="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/NAIS.py" />
         <option value="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Evaluate.py" />
         <option value="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/FISM.py" />
-        <option value="$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Batch_gen.py" />
-        <option value="$PROJECT_DIR$/.gitignore" />
       </list>
     </option>
   </component>
@@ -299,7 +311,15 @@
               <item name="tensorflow1.2" type="462c0819:PsiDirectoryNode" />
               <item name="recommendation" type="462c0819:PsiDirectoryNode" />
               <item name="Basic-NAIS-Demo" type="462c0819:PsiDirectoryNode" />
-              <item name="Data" type="462c0819:PsiDirectoryNode" />
+              <item name="Log" type="462c0819:PsiDirectoryNode" />
+            </path>
+            <path>
+              <item name="tensorflow1.2" type="b2602c69:ProjectViewProjectNode" />
+              <item name="tensorflow1.2" type="462c0819:PsiDirectoryNode" />
+              <item name="recommendation" type="462c0819:PsiDirectoryNode" />
+              <item name="Basic-NAIS-Demo" type="462c0819:PsiDirectoryNode" />
+              <item name="Log" type="462c0819:PsiDirectoryNode" />
+              <item name="pinterest-20" type="462c0819:PsiDirectoryNode" />
             </path>
           </expand>
           <select />
@@ -480,7 +500,7 @@
     <layout>
       <window_info id="TODO" active="false" anchor="bottom" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="false" show_stripe_button="true" weight="0.32889965" sideWeight="0.5" order="6" side_tool="false" content_ui="tabs" />
       <window_info id="Event Log" active="false" anchor="bottom" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="false" show_stripe_button="true" weight="0.33" sideWeight="0.5" order="7" side_tool="true" content_ui="tabs" />
-      <window_info id="Run" active="false" anchor="bottom" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="true" show_stripe_button="true" weight="0.42321643" sideWeight="0.5" order="2" side_tool="false" content_ui="tabs" />
+      <window_info id="Run" active="true" anchor="bottom" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="true" show_stripe_button="true" weight="0.29504234" sideWeight="0.5" order="2" side_tool="false" content_ui="tabs" />
       <window_info id="Version Control" active="false" anchor="bottom" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="false" show_stripe_button="true" weight="0.32889965" sideWeight="0.5" order="7" side_tool="false" content_ui="tabs" />
       <window_info id="Python Console" active="false" anchor="bottom" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="false" show_stripe_button="true" weight="0.32889965" sideWeight="0.5" order="7" side_tool="false" content_ui="tabs" />
       <window_info id="Terminal" active="false" anchor="bottom" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="false" show_stripe_button="true" weight="0.2031439" sideWeight="0.5" order="7" side_tool="false" content_ui="tabs" />
@@ -532,13 +552,6 @@
     <watches-manager />
   </component>
   <component name="editorHistoryManager">
-    <entry file="file://$PROJECT_DIR$/RL/Basic-NoisyNet-Demo/readme">
-      <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="15">
-          <caret line="1" column="12" lean-forward="true" selection-start-line="1" selection-start-column="12" selection-end-line="1" selection-end-column="12" />
-        </state>
-      </provider>
-    </entry>
     <entry file="file://$PROJECT_DIR$/RL/Basic-DisRL-Demo.py" />
     <entry file="file://$PROJECT_DIR$/RL/Double-DQN-demo/RL_brain.py">
       <provider selected="true" editor-type-id="text-editor">
@@ -596,13 +609,6 @@
         </state>
       </provider>
     </entry>
-    <entry file="file://$USER_HOME$/Anaconda/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/ops.py">
-      <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="161">
-          <caret line="569" column="0" lean-forward="false" selection-start-line="569" selection-start-column="0" selection-end-line="569" selection-end-column="0" />
-        </state>
-      </provider>
-    </entry>
     <entry file="file://$PROJECT_DIR$/RL/Basic-DisRL-Demo/Categorical_DQN.py">
       <provider selected="true" editor-type-id="text-editor">
         <state relative-caret-position="93">
@@ -853,61 +859,75 @@
         </state>
       </provider>
     </entry>
-    <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Dataset.py">
+    <entry file="file://$PROJECT_DIR$/.gitignore">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="195">
-          <caret line="13" column="63" lean-forward="false" selection-start-line="13" selection-start-column="63" selection-end-line="13" selection-end-column="63" />
-          <folding>
-            <element signature="e#0#25#0" expanded="true" />
-          </folding>
+        <state relative-caret-position="634">
+          <caret line="53" column="4" lean-forward="false" selection-start-line="53" selection-start-column="4" selection-end-line="53" selection-end-column="4" />
+          <folding />
         </state>
       </provider>
     </entry>
-    <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Evaluate.py">
+    <entry file="file://$USER_HOME$/Anaconda/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/ops.py">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="-213">
-          <caret line="68" column="19" lean-forward="false" selection-start-line="68" selection-start-column="19" selection-end-line="68" selection-end-column="19" />
+        <state relative-caret-position="209">
+          <caret line="1469" column="0" lean-forward="false" selection-start-line="1469" selection-start-column="0" selection-end-line="1469" selection-end-column="0" />
           <folding />
         </state>
       </provider>
     </entry>
-    <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/FISM.py">
+    <entry file="file://$USER_HOME$/Anaconda/anaconda/lib/python3.6/multiprocessing/__init__.py">
+      <provider selected="true" editor-type-id="text-editor">
+        <state relative-caret-position="255">
+          <caret line="18" column="33" lean-forward="true" selection-start-line="18" selection-start-column="33" selection-end-line="18" selection-end-column="33" />
+          <folding />
+        </state>
+      </provider>
+    </entry>
+    <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Dataset.py">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="2648">
-          <caret line="180" column="112" lean-forward="false" selection-start-line="180" selection-start-column="112" selection-end-line="180" selection-end-column="112" />
+        <state relative-caret-position="15">
+          <caret line="13" column="63" lean-forward="false" selection-start-line="13" selection-start-column="63" selection-end-line="13" selection-end-column="63" />
           <folding>
-            <element signature="e#0#38#0" expanded="true" />
+            <element signature="e#0#25#0" expanded="true" />
           </folding>
         </state>
       </provider>
     </entry>
     <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/NAIS.py">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="172">
-          <caret line="182" column="43" lean-forward="false" selection-start-line="182" selection-start-column="43" selection-end-line="182" selection-end-column="43" />
+        <state relative-caret-position="169">
+          <caret line="260" column="22" lean-forward="false" selection-start-line="260" selection-start-column="17" selection-end-line="260" selection-end-column="22" />
           <folding>
             <element signature="e#0#23#0" expanded="true" />
           </folding>
         </state>
       </provider>
     </entry>
-    <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Batch_gen.py">
+    <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Evaluate.py">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="192">
-          <caret line="109" column="54" lean-forward="false" selection-start-line="109" selection-start-column="54" selection-end-line="109" selection-end-column="54" />
-          <folding>
-            <element signature="e#0#22#0" expanded="true" />
-          </folding>
+        <state relative-caret-position="49">
+          <caret line="60" column="72" lean-forward="false" selection-start-line="60" selection-start-column="72" selection-end-line="60" selection-end-column="72" />
+          <folding />
         </state>
       </provider>
     </entry>
-    <entry file="file://$PROJECT_DIR$/.gitignore">
+    <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/Batch_gen.py">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="569">
-          <caret line="53" column="4" lean-forward="false" selection-start-line="53" selection-start-column="4" selection-end-line="53" selection-end-column="4" />
+        <state relative-caret-position="209">
+          <caret line="160" column="18" lean-forward="false" selection-start-line="160" selection-start-column="13" selection-end-line="160" selection-end-column="18" />
           <folding />
         </state>
       </provider>
     </entry>
+    <entry file="file://$PROJECT_DIR$/recommendation/Basic-NAIS-Demo/FISM.py">
+      <provider selected="true" editor-type-id="text-editor">
+        <state relative-caret-position="139">
+          <caret line="158" column="0" lean-forward="true" selection-start-line="158" selection-start-column="0" selection-end-line="158" selection-end-column="0" />
+          <folding>
+            <element signature="e#0#38#0" expanded="true" />
+          </folding>
+        </state>
+      </provider>
+    </entry>
   </component>
 </project>
\ No newline at end of file
diff --git a/recommendation/Basic-NAIS-Demo/Batch_gen.py b/recommendation/Basic-NAIS-Demo/Batch_gen.py
index c040e4c8..35484008 100644
--- a/recommendation/Basic-NAIS-Demo/Batch_gen.py
+++ b/recommendation/Basic-NAIS-Demo/Batch_gen.py
@@ -1,4 +1,3 @@
-import multiprocessing
 import numpy as np
 
 _Dataset = None
@@ -52,23 +51,13 @@ def batch_gen(batches, i):
 
 def _preprocess(get_train_batch):  # generate the masked batch list
     user_input_list, num_idx_list, item_input_list, labels_list = [], [], [], []
-    cpu_count = multiprocessing.cpu_count()
-    if cpu_count == 1:
-        for i in range(_num_batch):
-            ui, ni, ii, l = get_train_batch(i)
-            user_input_list.append(ui)
-            num_idx_list.append(ni)
-            item_input_list.append(ii)
-            labels_list.append(l)
-    else:
-        pool = multiprocessing.Pool(cpu_count)
-        res = pool.map(get_train_batch, list(range(_num_batch)))
-        pool.close()
-        pool.join()
-        user_input_list = [r[0] for r in res]
-        num_idx_list = [r[1] for r in res]
-        item_input_list = [r[2] for r in res]
-        labels_list = [r[3] for r in res]
+
+    for i in range(_num_batch):
+        ui, ni, ii, l = get_train_batch(i)
+        user_input_list.append(ui)
+        num_idx_list.append(ni)
+        item_input_list.append(ii)
+        labels_list.append(l)
     return (user_input_list, num_idx_list, item_input_list, labels_list)
 
 
diff --git a/recommendation/Basic-NAIS-Demo/Evaluate.py b/recommendation/Basic-NAIS-Demo/Evaluate.py
index 05dfc67f..4b3d98ba 100644
--- a/recommendation/Basic-NAIS-Demo/Evaluate.py
+++ b/recommendation/Basic-NAIS-Demo/Evaluate.py
@@ -58,7 +58,7 @@ def eval(model, sess, testRatings, testNegatives, DictList):
     hits, ndcgs, losses = [],[],[]
     if(num_thread > 1): # Multi-thread
         pool = multiprocessing.Pool(num_thread)
-        res = pool.map(_eval_one_rating, range(len(_testRatings)))
+        res = pool.map(_eval_one_rating, list(range(len(_testRatings))))
         pool.close()
         pool.join()
         hits = [r[0] for r in res]
diff --git a/recommendation/Basic-NAIS-Demo/FISM.py b/recommendation/Basic-NAIS-Demo/FISM.py
index 5fd4f462..aaf26bc0 100644
--- a/recommendation/Basic-NAIS-Demo/FISM.py
+++ b/recommendation/Basic-NAIS-Demo/FISM.py
@@ -79,7 +79,7 @@ def _create_placeholders(self):
             self.labels = tf.placeholder(tf.float32, shape=[None, 1])  # the ground truth
 
     def _create_variables(self):
-        with tf.name_scope("embedding"):  # The embedding initialization is unknown now
+        with tf.variable_scope("embedding"):  # The embedding initialization is unknown now
             self.c1 = tf.Variable(
                 tf.truncated_normal(shape=[self.num_items, self.embedding_size], mean=0.0, stddev=0.01),
                 # why [0, 3707)?
@@ -136,6 +136,10 @@ def training(flag, model, dataset, epochs, num_negatives):
                 saver.restore(sess, ckpt.model_checkpoint_path)
                 logging.info("using pretrained variables")
                 print("using pretrained variables")
+            else:
+                sess.run(tf.global_variables_initializer())
+                logging.info("initialized")
+                print("initialized")
         else:
             sess.run(tf.global_variables_initializer())
             logging.info("initialized")
@@ -147,7 +151,7 @@ def training(flag, model, dataset, epochs, num_negatives):
         batch_time = time() - batch_begin
 
         num_batch = len(batches[1])
-        batch_index = range(num_batch)
+        batch_index = list(range(num_batch))
 
         # initialize the evaluation feed_dicts
         testDict = evaluate.init_evaluate_model(model, sess, dataset.testRatings, dataset.testNegatives,
diff --git a/recommendation/Basic-NAIS-Demo/NAIS.py b/recommendation/Basic-NAIS-Demo/NAIS.py
index 5546f96f..c1c5496d 100644
--- a/recommendation/Basic-NAIS-Demo/NAIS.py
+++ b/recommendation/Basic-NAIS-Demo/NAIS.py
@@ -52,8 +52,9 @@ def parse_args():
                         help='0 for NAIS_prod, 1 for NAIS_concat')
     return parser.parse_args()
 
-class NAIS(object):
-    def __init__(self,num_items,args):
+
+class NAIS:
+    def __init__(self, num_items, args):
         self.pretrain = args.pretrain
         self.num_items = num_items
         self.dataset_name = args.dataset
@@ -73,7 +74,6 @@ def __init__(self,num_items,args):
         self.eta_bilinear = regs[2]
         self.train_loss = args.train_loss
 
-
     def _create_placeholders(self):
         with tf.name_scope("input_data"):
             self.user_input = tf.placeholder(tf.int32, shape=[None, None])  # the index of users
@@ -82,7 +82,7 @@ def _create_placeholders(self):
             self.labels = tf.placeholder(tf.float32, shape=[None, 1])  # the ground truth
 
     def _create_variables(self):
-        with tf.name_scope("embedding"):
+        with tf.variable_scope("embedding"):  # The embedding initialization is unknown now
             trainable_flag = (self.pretrain != 2)
             self.c1 = tf.Variable(
                 tf.truncated_normal(shape=[self.num_items, self.embedding_size], mean=0.0, stddev=0.01), name='c1',
@@ -94,7 +94,7 @@ def _create_variables(self):
                 name='embedding_Q', dtype=tf.float32, trainable=trainable_flag)
             self.bias = tf.Variable(tf.zeros(self.num_items), name='bias', trainable=trainable_flag)
 
-            # Variables for attention,两种计算attention的方式
+            # Variables for attention
             if self.algorithm == 0:
                 self.W = tf.Variable(tf.truncated_normal(shape=[self.embedding_size, self.weight_size], mean=0.0,
                                                          stddev=tf.sqrt(
@@ -110,13 +110,12 @@ def _create_variables(self):
                                  trainable=True)
             self.h = tf.Variable(tf.ones([self.weight_size, 1]), name='H_for_MLP', dtype=tf.float32)
 
-    def _attention_MLP(self,q_):
+    def _attention_MLP(self, q_):
         with tf.name_scope("attention_MLP"):
             b = tf.shape(q_)[0]
             n = tf.shape(q_)[1]
             r = (self.algorithm + 1) * self.embedding_size
 
-            # 得到attention 的值
             MLP_output = tf.matmul(tf.reshape(q_, [-1, r]), self.W) + self.b  # (b*n, e or 2*e) * (e or 2*e, w) + (1, w)
             if self.activation == 0:
                 MLP_output = tf.nn.relu(MLP_output)
@@ -129,20 +128,20 @@ def _attention_MLP(self,q_):
 
             # softmax for not mask features
             exp_A_ = tf.exp(A_)
-            num_idx = tf.reduce_sum(self.num_idx, 1) # 每个人有多少个评分
-            mask_mat = tf.sequence_mask(num_idx, maxlen=n, dtype=tf.float32)  # (b, n) 加入mask
-            exp_A_ = mask_mat * exp_A_ # 填充的位置变为0
+            num_idx = tf.reduce_sum(self.num_idx, 1)
+            mask_mat = tf.sequence_mask(num_idx, maxlen=n, dtype=tf.float32)  # (b, n)
+            exp_A_ = mask_mat * exp_A_
             exp_sum = tf.reduce_sum(exp_A_, 1, keep_dims=True)  # (b, 1)
-            exp_sum = tf.pow(exp_sum, tf.constant(self.beta, tf.float32, [1])) # 进行压缩
+            exp_sum = tf.pow(exp_sum, tf.constant(self.beta, tf.float32, [1]))
 
             A = tf.expand_dims(tf.div(exp_A_, exp_sum), 2)  # (b, n, 1)
 
-            return tf.reduce_sum(A * self.embedding_q_, 1) # 得到
+            return tf.reduce_sum(A * self.embedding_q_, 1)
 
     def _create_inference(self):
         with tf.name_scope("inference"):
-            self.embedding_q_ = tf.nn.embedding_lookup(self.embedding_Q_, self.user_input)  # (b, n, e) # 历史评分
-            self.embedding_q = tf.nn.embedding_lookup(self.embedding_Q, self.item_input)  # (b, 1, e) # 目标
+            self.embedding_q_ = tf.nn.embedding_lookup(self.embedding_Q_, self.user_input)  # (b, n, e)
+            self.embedding_q = tf.nn.embedding_lookup(self.embedding_Q, self.item_input)  # (b, 1, e)
 
             if self.algorithm == 0:
                 self.embedding_p = self._attention_MLP(self.embedding_q_ * self.embedding_q)
@@ -162,7 +161,7 @@ def _create_loss(self):
             self.loss = tf.losses.log_loss(self.labels, self.output) + \
                         self.lambda_bilinear * tf.reduce_sum(tf.square(self.embedding_Q)) + \
                         self.gamma_bilinear * tf.reduce_sum(tf.square(self.embedding_Q_)) + \
-                        self.eta_bilinear * tf.reduce_sum(tf.square(self.W)) # logloss + l2正则
+                        self.eta_bilinear * tf.reduce_sum(tf.square(self.W))
 
     def _create_optimizer(self):
         with tf.name_scope("optimizer"):
@@ -191,6 +190,10 @@ def training(flag, model, dataset, epochs, num_negatives):
                 saver.restore(sess, ckpt.model_checkpoint_path)
                 logging.info("using pretrained variables")
                 print("using pretrained variables")
+            else:
+                sess.run(tf.global_variables_initializer())
+                logging.info("initialized")
+                print("initialized")
         else:
             sess.run(tf.global_variables_initializer())
             logging.info("initialized")
@@ -202,7 +205,7 @@ def training(flag, model, dataset, epochs, num_negatives):
         batch_time = time() - batch_begin
 
         num_batch = len(batches[1])
-        batch_index = range(num_batch)
+        batch_index = list(range(num_batch))
 
         # initialize the evaluation feed_dicts
         testDict = evaluate.init_evaluate_model(model, sess, dataset.testRatings, dataset.testNegatives,