04151309

models_processing/model_tf/tf_lstm2_pre.py

@@ -19,10 +19,10 @@ from itertools import chain
 from common.logs import Log
 from tf_lstm import TSHandler
 # logger = Log('tf_bp').logger()
-logger = Log('tf_ts').logger
+logger = Log('tf_ts2').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')
+app = Flask('tf_lstm2_pre——service')
 
 current_dir = os.path.dirname(os.path.abspath(__file__))
 with open(os.path.join(current_dir, 'lstm.yaml'), 'r', encoding='utf-8') as f:

models_processing/model_tf/tf_lstm2_train.py

@@ -15,9 +15,9 @@ from copy import deepcopy
 from models_processing.model_tf.tf_lstm import TSHandler
 from common.database_dml_koi import *
 from common.logs import Log
-logger = Log('tf_ts').logger
+logger = Log('tf_ts2').logger
 np.random.seed(42)  # NumPy随机种子
-app = Flask('tf_lstm_train——service')
+app = Flask('tf_lstm2_train——service')
 
 current_dir = os.path.dirname(os.path.abspath(__file__))
 with open(os.path.join(current_dir, 'lstm.yaml'), 'r', encoding='utf-8') as f:

models_processing/model_tf/tf_lstm3_pre.py

@@ -18,11 +18,10 @@ model_lock = Lock()
 from itertools import chain
 from common.logs import Log
 from tf_lstm import TSHandler
-# logger = Log('tf_bp').logger()
-logger = Log('tf_ts').logger
+logger = Log('tf_ts3').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')
+app = Flask('tf_lstm3_pre——service')
 
 current_dir = os.path.dirname(os.path.abspath(__file__))
 with open(os.path.join(current_dir, 'lstm.yaml'), 'r', encoding='utf-8') as f:
@@ -103,7 +102,7 @@ def model_prediction_bp():
 if __name__ == "__main__":
     print("Program starts execution!")
     from waitress import serve
-    serve(app, host="0.0.0.0", port=10120,
+    serve(app, host="0.0.0.0", port=10122,
           threads=8,  # 指定线程数（默认4，根据硬件调整）
           channel_timeout=600  # 连接超时时间（秒）
           )

models_processing/model_tf/tf_lstm3_train.py

@@ -15,9 +15,9 @@ from copy import deepcopy
 from models_processing.model_tf.tf_lstm import TSHandler
 from common.database_dml_koi import *
 from common.logs import Log
-logger = Log('tf_ts').logger
+logger = Log('tf_ts3').logger
 np.random.seed(42)  # NumPy随机种子
-app = Flask('tf_lstm_train——service')
+app = Flask('tf_lstm3_train——service')
 
 current_dir = os.path.dirname(os.path.abspath(__file__))
 with open(os.path.join(current_dir, 'lstm.yaml'), 'r', encoding='utf-8') as f:
@@ -95,7 +95,7 @@ def model_training_bp():
 if __name__ == "__main__":
     print("Program starts execution!")
     from waitress import serve
-    serve(app, host="0.0.0.0", port=10119,
+    serve(app, host="0.0.0.0", port=10121,
           threads=8,  # 指定线程数（默认4，根据硬件调整）
           channel_timeout=600  # 连接超时时间（秒）
           )