完成实验3任务1

Lab3/code/1.1.py

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+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):
+        super().__init__()
+        self.p = p
+        self.mask = None
+
+    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)
+        else:
+            return x
+
+
+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],
+                      [6.0, 7.0, 8.0, 9.0, 10.0]])
+    print(f"输入：\n{x}")
+    output_my_dropout = my_dropout(x)
+    output_nn_dropout = nn_dropout(x)
+    print(f"My_Dropout输出：\n{output_my_dropout}")
+    print(f"nn.Dropout输出：\n{output_nn_dropout}")