03101305

models_processing/model_koi/tf_bp_pre.py

@@ -88,7 +88,6 @@ def model_prediction_bp():
 if __name__ == "__main__":
     print("Program starts execution!")
     from waitress import serve
-
     serve(app, host="0.0.0.0", port=10110)
     print("server start!")
 

models_processing/model_koi/tf_bp_train.py

@@ -77,10 +77,7 @@ def model_training_bp():
 
 if __name__ == "__main__":
     print("Program starts execution!")
-    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    logger = logging.getLogger("model_training_bp log")
     from waitress import serve
-
     serve(app, host="0.0.0.0", port=10111)
     # print("server start!")
     # args_dict = {"mongodb_database": 'david_test', 'scaler_table': 'j00083_scaler', 'model_name': 'bp1.0.test',

models_processing/model_koi/tf_cnn_pre.py

@@ -18,7 +18,7 @@ from itertools import chain
 from common.logs import Log
 from tf_cnn import CNNHandler
 # logger = Log('tf_bp').logger()
-logger = Log('tf_bp').logger
+logger = Log('tf_cnn').logger
 np.random.seed(42)  # NumPy随机种子
 # tf.set_random_seed(42)  # TensorFlow随机种子
 app = Flask('tf_cnn_pre——service')
@@ -88,10 +88,7 @@ def model_prediction_bp():
 
 if __name__ == "__main__":
     print("Program starts execution!")
-    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    logger = logging.getLogger("model_training_bp log")
     from waitress import serve
-
     serve(app, host="0.0.0.0", port=10112)
     print("server start!")
 

models_processing/model_koi/tf_cnn_train.py

@@ -15,8 +15,8 @@ from models_processing.model_koi.tf_cnn import CNNHandler
 from common.database_dml_koi import *
 import matplotlib.pyplot as plt
 from common.logs import Log
-logger = logging.getLogger()
-# logger = Log('models-processing').logger
+# logger = logging.getLogger()
+logger = Log('tf_cnn').logger
 np.random.seed(42)  # NumPy随机种子
 # tf.set_random_seed(42)  # TensorFlow随机种子
 app = Flask('tf_cnn_train——service')
@@ -80,10 +80,7 @@ def model_training_bp():
 
 if __name__ == "__main__":
     print("Program starts execution!")
-    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    logger = logging.getLogger("model_training_bp log")
     from waitress import serve
-
     serve(app, host="0.0.0.0", port=10113)
     # print("server start!")
     # args_dict = {"mongodb_database": 'david_test', 'scaler_table': 'j00083_scaler', 'model_name': 'bp1.0.test',

models_processing/model_koi/tf_lstm_pre.py

@@ -18,7 +18,7 @@ from itertools import chain
 from common.logs import Log
 from tf_lstm import TSHandler
 # logger = Log('tf_bp').logger()
-logger = Log('tf_bp').logger
+logger = Log('tf_ts').logger
 np.random.seed(42)  # NumPy随机种子
 # tf.set_random_seed(42)  # TensorFlow随机种子
 app = Flask('tf_lstm_pre——service')
@@ -87,10 +87,7 @@ def model_prediction_bp():
 
 if __name__ == "__main__":
     print("Program starts execution!")
-    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    logger = logging.getLogger("model_training_bp log")
     from waitress import serve
-
     serve(app, host="0.0.0.0", port=10114)
     print("server start!")
 

models_processing/model_koi/tf_lstm_train.py

@@ -14,8 +14,7 @@ import time, yaml, threading
 from models_processing.model_koi.tf_lstm import TSHandler
 from common.database_dml_koi import *
 from common.logs import Log
-logger = logging.getLogger()
-# logger = Log('models-processing').logger
+logger = Log('tf_ts').logger
 np.random.seed(42)  # NumPy随机种子
 # tf.set_random_seed(42)  # TensorFlow随机种子
 app = Flask('tf_lstm_train——service')
@@ -76,10 +75,7 @@ def model_training_bp():
 
 if __name__ == "__main__":
     print("Program starts execution!")
-    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
-    logger = logging.getLogger("model_training_bp log")
     from waitress import serve
-
     serve(app, host="0.0.0.0", port=10115)
     print("server start!")
     # args_dict = {"mongodb_database": 'realtimeDq', 'scaler_table': 'j00600_scaler', 'model_name': 'lstm1',