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model.py

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+import torch
+import torch.nn as nn
+
+class TremorCNN(nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.conv = nn.Sequential(
+            nn.Conv2d(1, 16, kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.MaxPool2d(2),
+
+            nn.Conv2d(16, 32, kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.MaxPool2d(2),
+        )
+
+        self.fc = nn.Sequential(
+            nn.Dropout(0.5),
+            nn.Linear(704, 64),
+            nn.ReLU(),
+            nn.Dropout(0.3),
+            nn.Linear(64, 1),
+        )
+
+    def forward(self, x):
+        x = self.conv(x)
+        x = x.view(x.size(0), -1)
+        x = self.fc(x)
+        return x