Create day4.py

Tasks/daily tasks/Ananthu Ajay/day4.py

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+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+
+class Net(nn.Module):
+
+    def __init__(self):
+        super(Net, self).__init__()
+        self.conv1 = nn.Conv2d(1, 4, 4)
+        self.conv2 = nn.Conv2d(4, 16, 4)
+        self.fc1 = nn.Linear(16 * 4 * 4, 120)
+        self.fc2 = nn.Linear(120, 10)
+
+    def forward(self, x):
+        x = F.max_pool2d(F.sigmoid(self.conv1(x)), (2, 2))
+        x = F.max_pool2d(F.sigmoid(self.conv2(x)), 2)
+        x = x.view(-1, self.num_flat_features(x))
+        x = F.sigmoid(self.fc1(x))
+        x = self.fc2(x)
+        return x
+
+    def num_flat_features(self, x):
+        size = x.size()[1:]
+        num_features = 1
+        for s in size:
+            num_features *= s
+        return num_features
+
+
+net = Net()
+print(net)