54 lines
1.5 KiB
Python
54 lines
1.5 KiB
Python
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"""
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药店销售预测系统 - 全局配置参数
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"""
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import torch
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import matplotlib
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matplotlib.use('Agg') # 设置matplotlib后端为Agg，适用于无头服务器环境
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import matplotlib.pyplot as plt
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import os
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# 解决画图中文显示问题
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plt.rcParams['font.sans-serif'] = ['SimHei']
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plt.rcParams['axes.unicode_minus'] = False
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# 获取设备（GPU或CPU）
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def get_device():
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"""获取可用的计算设备（GPU或CPU）"""
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if torch.cuda.is_available():
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return torch.device('cuda')
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else:
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return torch.device('cpu')
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# 全局设备
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DEVICE = get_device()
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# 数据相关配置
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DEFAULT_DATA_PATH = 'pharmacy_sales.xlsx'
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DEFAULT_MODEL_DIR = 'saved_models'
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DEFAULT_FEATURES = ['sales', 'price', 'weekday', 'month', 'is_holiday', 'is_weekend', 'is_promotion', 'temperature']
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# 时间序列参数
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LOOK_BACK = 14 # 使用过去14天数据
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FORECAST_HORIZON = 7 # 预测未来7天销量
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# 训练参数
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DEFAULT_EPOCHS = 50 # 训练轮次
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DEFAULT_BATCH_SIZE = 32 # 批大小
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DEFAULT_LEARNING_RATE = 0.001 # 学习率
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# 模型参数
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NUM_FEATURES = 8 # 输入特征数
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EMBED_DIM = 32 # 嵌入维度
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DENSE_DIM = 32 # 隐藏层神经元数
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NUM_HEADS = 4 # 注意力头数
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DROPOUT_RATE = 0.1 # 丢弃率
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NUM_BLOCKS = 3 # 编码器解码器数
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HIDDEN_SIZE = 64 # 隐藏层大小
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NUM_LAYERS = 2 # 层数
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# 支持的模型类型
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SUPPORTED_MODELS = ['mlstm', 'kan', 'transformer', 'tcn', 'optimized_kan']
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# 创建模型保存目录
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os.makedirs(DEFAULT_MODEL_DIR, exist_ok=True)
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