Create model.py

model.py

@@ -0,0 +1,19 @@
+import torch.nn as nn
+import torchvision.models as models
+
+class CNNLSTMClassifier(nn.Module):
+    def __init__(self, hidden_dim=128, num_classes=2):
+        super().__init__()
+        resnet = models.resnet18(weights=models.ResNet18_Weights.DEFAULT)
+        self.cnn = nn.Sequential(*list(resnet.children())[:-1])
+        self.cnn_out_dim = 512
+        self.lstm = nn.LSTM(self.cnn_out_dim, hidden_dim, batch_first=True)
+        self.fc = nn.Linear(hidden_dim, num_classes)
+
+    def forward(self, x):
+        B, T, C, H, W = x.shape
+        x = x.view(B * T, C, H, W)
+        with torch.no_grad():
+            cnn_out = self.cnn(x).view(B, T, -1)
+        lstm_out, _ = self.lstm(cnn_out)
+        return self.fc(lstm_out[:, -1, :])