新建仓库维护数据预测项目

FC_ML_NN/NN_Basic.py

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+import torch
+import torch.nn as nn
+import torch.optim as optim
+import numpy as np
+import matplotlib.pyplot as plt
+
+# 数据生成
+x = np.linspace(-3, 3, 100).reshape(-1, 1)
+y = 2 * x + 1 + np.random.normal(0, 0.5, x.shape)
+x_tensor = torch.FloatTensor(x)
+y_tensor = torch.FloatTensor(y)
+
+# 模型定义
+class LinearModel(nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.linear = nn.Linear(1, 1)
+    def forward(self, x):
+        return self.linear(x)
+
+# 训练配置
+model = LinearModel()
+criterion = nn.MSELoss()
+optimizer = optim.SGD(model.parameters(), lr=0.01)
+
+# 训练循环
+for epoch in range(1000):
+    pred = model(x_tensor)
+    loss = criterion(pred, y_tensor)
+    optimizer.zero_grad()
+    loss.backward()
+    optimizer.step()
+
+# 结果输出
+w = model.linear.weight.item()
+b = model.linear.bias.item()
+print(f'Final equation: y = {w:.2f}x + {b:.2f}')
+
+# 可视化
+plt.scatter(x, y)
+plt.plot(x, w*x + b, 'r-')
+plt.show()