independent_test

fl_code/#svm/basic.sh

@@ -0,0 +1,54 @@
+#!/bin/bash
+# Desc: ALL Client
+
+sub_path=lib/python3.7/site-packages/flwr/common/parameter.py
+root_path=`which python | sed 's@/bin/python@/@g'`
+path=$root_path$sub_path
+sed -r -i '28s/#+tensors/tensors/g' $path
+sed -i '29s/tensors/#tensors/g' $path
+
+file_name=server_IP
+client_num=$1
+
+port=8080
+
+if [ ! -d ./log/all/ ]; then
+  mkdir -p ./log/all/
+fi
+rm -f ./log/all/*
+[ -f ./$file_name ] && rm -f $file_name
+
+while true; do
+  ss -tlnp | grep $port > /dev/null
+  if [ $? -eq 0 ]; then
+    let port++
+  else
+    break
+  fi
+done
+
+nohup python svm_server.py $port $client_num >./log/all/server.log 2>&1 &
+if [ $? -eq 0 ]; then
+  echo "submit svm_server $port"
+else
+  echo "submit svm_server error" && exit
+fi
+
+count=0
+while [ ! -f ./$file_name ] && (($count < 10)); do
+  sleep 6
+  let count++
+done
+
+(($count >= 10)) && echo "no find $file_name" && exit
+
+for ((i = 0; i <= $client_num - 1; i++)); do
+  nohup python svm_client.py $i -1 >./log/all/client$i.log 2>&1 &
+  if [ $? -eq 0 ]; then
+    echo "submit svm_client $i"
+  else
+    echo "submit svm_client $i error" && exit
+  fi
+done
+
+echo "all task submitted"

fl_code/#svm/contribution_assessment.sh

@@ -0,0 +1,62 @@
+#!/bin/bash
+# Desc: ALL Client
+
+sub_path=lib/python3.7/site-packages/flwr/common/parameter.py
+root_path=`which python | sed 's@/bin/python@/@g'`
+path=$root_path$sub_path
+sed -r -i '28s/#+tensors/tensors/g' $path
+sed -i '29s/tensors/#tensors/g' $path
+
+file_name=server_IP
+client_num=$1
+
+port=8080
+[ -f ./$file_name ] && rm -f $file_name
+
+for ((i = 0; i < $client_num; i++)); do
+
+  if [ ! -d ./log/lack_$i/ ]; then
+    mkdir -p ./log/lack_$i/
+  fi
+  rm -f ./log/lack_$i/*
+
+  while true; do
+    ss -tlnp | grep $port > /dev/null
+    if [ $? -eq 0 ]; then
+      let port++
+    else
+      break
+    fi
+  done
+
+  nohup python svm_server.py $port $(($client_num - 1)) >./log/lack_$i/server.log 2>&1 &
+  if [ $? -eq 0 ]; then
+    echo "submit svm_server $port"
+  else
+    echo "submit svm_server error" && exit
+  fi
+
+  count=0
+  while [ ! -f ./$file_name ] && (($count < 10)); do
+    sleep 6
+    let count++
+  done
+
+  (($count >= 10)) && echo "no find $file_name" && exit
+
+  for ((j = 0; j <= $(($client_num - 1)); j++)); do
+    [ $j -eq $i ] && continue
+    nohup python svm_client.py $j $i >./log/lack_$i/client$j.log 2>&1 &
+    if [ $? -eq 0 ]; then
+      echo "submit svm_client $j"
+    else
+      echo "submit svm_client $j error" && exit
+    fi
+  done
+
+  echo "lack $i _client Contribution assessment task submitted"
+  sleep 10
+
+done
+
+echo "all task submitted"

fl_code/svm/svm_client.py → fl_code/#svm/svm_client.py

@@ -86,6 +86,6 @@ def evaluate(self, parameters, config):
     model = SVC(kernel="linear", cache_size=50000, class_weight = "balanced")
     model.fit(x1, y1)
     local_test()
-    independent_test(logger, model, path, client_id)
+    independent_test(logger, model, client_id)
     logger.info('#end')
 

fl_code/all_center.py

@@ -20,7 +20,7 @@
 def RandomForest():
     clf = RandomForestClassifier(random_state=0,class_weight='balanced',max_depth=7,n_estimators=20)
     clf = clf.fit(Xtrain, Ytrain)
-    independent_test(logger, clf, dir_path, 'all')
+    independent_test(logger, clf, 'all')
 
 def Logistic():
     model = LogisticRegression(penalty="l2",class_weight='balanced',max_iter=5000, warm_start=True)
@@ -29,15 +29,15 @@ def Logistic():
     ss = StandardScaler()
     ss = ss.fit(x_train.loc[:, col])
     x_train.loc[:, col] = ss.transform(x_train.loc[:, col])
-    model=model.fit(Xtrain, Ytrain)
-    independent_test(logger, model, dir_path, 'all')
+    model=model.fit(x_train, Ytrain)
+    independent_test(logger, model, 'all')
 
 
 def xgboost():
     weight = (Ytrain == 0).sum() / (Ytrain == 1).sum()
     model = XGBClassifier(learning_rate=0.1, n_estimators=20,scale_pos_weight=weight)
     model.fit(Xtrain, Ytrain)
-    independent_test(logger, model, dir_path, 'all')
+    independent_test(logger, model,  'all')
 
 def SVM():
     model = SVC(kernel="linear",class_weight = "balanced", cache_size=10000,probability=True)
@@ -51,7 +51,7 @@ def SVM():
     x_test.loc[:, col] = ss.transform(x_test.loc[:, col])
 
     model = model.fit(x_train, Ytrain)
-    independent_test(logger, model, dir_path, 'all')
+    independent_test(logger, model,'all')
 
 def MLP():
     model = MLPClassifier(hidden_layer_sizes=(200,200),max_iter=200,random_state=0)
@@ -66,7 +66,7 @@ def MLP():
     ros = RandomOverSampler(random_state=0)
     x_train_resampled, Ytrain_resampled = ros.fit_resample(x_train, Ytrain)
     model = model.fit(x_train_resampled, Ytrain_resampled)
-    independent_test(logger, model, dir_path, 'all')
+    independent_test(logger, model,  'all')
 
 if __name__ == "__main__":
     dir_path=yaml.load(open('../config.yaml'),Loader=yaml.FullLoader)['use_data_dir_path']

fl_code/mlp/mlp_client.py

@@ -81,7 +81,7 @@ def evaluate(self, parameters, config):
 
     fl.client.start_numpy_client(server_ip, client=Client())
     local_test()
-    independent_test(logger, model, path, client_id)
+    independent_test(logger, model,client_id)
     logger.info('#end')
 
 

fl_code/randomforest/randomforest_client.py

@@ -150,5 +150,5 @@ def predict_proba(self, Xtest):
     fl.client.start_numpy_client(server_ip, client=client)
 
     local_test()
-    independent_test(logger, client, path, client_id)
+    independent_test(logger, client,client_id)
     logger.info('#end')

fl_code/single_center.py

@@ -25,7 +25,7 @@ def RandomForest(cur_client):
     logger.info('test_method: {} start'.format('local_test'))
     result_log(logger, Ytest, y_pred, y_score)
     logger.info('test_method: {} end'.format('local_test'))
-    independent_test(logger, model, dir_path, cur_client)
+    independent_test(logger, model, cur_client)
     year_by_year_test(cur_client, logger, model, dir_path)
 
 def Logistic(cur_client):
@@ -44,7 +44,7 @@ def Logistic(cur_client):
     logger.info('test_method: {} start'.format('local_test'))
     result_log(logger, Ytest, y_pred, y_score)
     logger.info('test_method: {} end'.format('local_test'))
-    independent_test(logger, model, dir_path, cur_client)
+    independent_test(logger, model,  cur_client)
     year_by_year_test(cur_client, logger, model, dir_path)
 
 def SVM(cur_client):
@@ -63,7 +63,7 @@ def SVM(cur_client):
     logger.info('test_method: {} start'.format('local_test'))
     result_log(logger, Ytest, y_pred, y_score)
     logger.info('test_method: {} end'.format('local_test'))
-    independent_test(logger, model, dir_path, cur_client)
+    independent_test(logger, model, cur_client)
     year_by_year_test(cur_client, logger, model, dir_path)
 
 def xgboost(cur_client):
@@ -75,7 +75,7 @@ def xgboost(cur_client):
     logger.info('test_method: {} start'.format('local_test'))
     result_log(logger, Ytest, y_pred, y_score)
     logger.info('test_method: {} end'.format('local_test'))
-    independent_test(logger, model, dir_path, cur_client)
+    independent_test(logger, model,  cur_client)
     year_by_year_test(cur_client, logger, model, dir_path)
 
 def MLP(cur_client):
@@ -96,7 +96,7 @@ def MLP(cur_client):
     logger.info('test_method: {} start'.format('local_test'))
     result_log(logger, Ytest, y_pred, y_score)
     logger.info('test_method: {} end'.format('local_test'))
-    independent_test(logger, model, dir_path, cur_client)
+    independent_test(logger, model, cur_client)
     year_by_year_test(cur_client, logger, model, dir_path)
 
 if __name__ == "__main__":

fl_code/xgboost/xgboost_client.py

@@ -263,5 +263,5 @@ def evaluate(self, parameters, config):
     fl.client.start_numpy_client(server_ip, client=client)
 
     local_test()
-    independent_test(logger, client, path, client_id)
+    independent_test(logger, client,client_id)
     logger.info('#end')