aa

梯度下降/aa.py

@@ -1,39 +0,0 @@
-import torch
-import torch.optim
-import matplotlib.pyplot as plt
-
-
-def f(x):
-      return x**2-3
-
-def df(x):
-      return 2*x
-def plotf(loss):
-      x = range(len(loss))
-      plt.plot(x,loss)
-      plt.xlabel('Iteration')
-      plt.ylabel('Loss')
-      plt.show()
-
-
-
-def main():
-      x = torch.tensor([15.],requires_grad=True)
-      optimizer = torch.optim.SGD([x,],lr = 0.1,momentum=0.9)
-      steps = 400
-      loss = []
-      for i in range(steps):
-            optimizer.zero_grad()
-            f(x).backward()
-            optimizer.step()
-            loss.append(f(x))
-            print(loss[i])
-      y = f(x)
-      print("函数最小值是： ",y)
-      plotf(loss)
-
-
-
-if __name__ == '__main__':
-    main()
-