完成实验三

Lab3/code/1.1.py

@@ -1,14 +1,7 @@
-import time
-import numpy as np
 import torch
-from torch.nn.functional import *
-from torch.utils.data import Dataset, DataLoader
 from torch import nn
-from torchvision import datasets, transforms
-from tqdm import tqdm
 from utils import *
 
-import ipdb
 
 class My_Dropout(nn.Module):
     def __init__(self, p, **kwargs):
@@ -16,7 +9,7 @@ class My_Dropout(nn.Module):
         self.p = p
         self.mask = None
 
-    def forward(self, x:torch.Tensor):
+    def forward(self, x: torch.Tensor):
         if self.training:
             self.mask = (torch.rand(x.shape) > self.p).to(dtype=torch.float32, device=x.device)
             return x * self.mask / (1 - self.p)
@@ -27,7 +20,7 @@ class My_Dropout(nn.Module):
 if __name__ == "__main__":
     my_dropout = My_Dropout(p=0.5)
     nn_dropout = nn.Dropout(p=0.5)
-    x = torch.tensor([[1.0, 2.0, 3.0, 4.0, 5.0],
+    x = torch.tensor([[1.0, 2.0, 3.0, 4.0, 5.0], 
                       [6.0, 7.0, 8.0, 9.0, 10.0]])
     print(f"输入：\n{x}")
     output_my_dropout = my_dropout(x)