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@@ -17,7 +17,6 @@ model_lock = Lock()
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from itertools import chain
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from common.logs import Log
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from tf_bp import BPHandler
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-# logger = Log('tf_bp').logger()
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logger = Log('tf_bp').logger
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np.random.seed(42) # NumPy随机种子
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# tf.set_random_seed(42) # TensorFlow随机种子
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@@ -88,17 +87,15 @@ def model_prediction_bp():
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if __name__ == "__main__":
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print("Program starts execution!")
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- logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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- logger = logging.getLogger("model_training_bp log")
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from waitress import serve
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serve(app, host="0.0.0.0", port=10110)
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print("server start!")
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# ------------------------测试代码------------------------
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- args_dict = {"mongodb_database": 'david_test', 'scaler_table': 'j00083_scaler', 'model_name': 'bp1.0.test',
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- 'model_table': 'j00083_model', 'mongodb_read_table': 'j00083_test', 'col_time': 'date_time', 'mongodb_write_table': 'j00083_rs',
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- 'features': 'speed10,direction10,speed30,direction30,speed50,direction50,speed70,direction70,speed90,direction90,speed110,direction110,speed150,direction150,speed170,direction170'}
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+ # args_dict = {"mongodb_database": 'david_test', 'scaler_table': 'j00083_scaler', 'model_name': 'bp1.0.test',
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+ # 'model_table': 'j00083_model', 'mongodb_read_table': 'j00083_test', 'col_time': 'date_time', 'mongodb_write_table': 'j00083_rs',
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+ # 'features': 'speed10,direction10,speed30,direction30,speed50,direction50,speed70,direction70,speed90,direction90,speed110,direction110,speed150,direction150,speed170,direction170'}
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# args_dict['features'] = args_dict['features'].split(',')
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# arguments.update(args_dict)
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# dh = DataHandler(logger, arguments)
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David