Update TumorModel.py

TumorModel.py

@@ -1,48 +1,13 @@
-import torch.nn as nn
-
-# 🧠 Tumor Type Classification Model
-class TumorClassification(nn.Module):
-    def __init__(self):
-        super(TumorClassification, self).__init__()
-        self.con1d = nn.Conv2d(1, 32, kernel_size=3, stride=1, padding=1)
-        self.relu1 = nn.ReLU()
-        self.pool1 = nn.MaxPool2d(2)
-
-        self.con2d = nn.Conv2d(32, 64, kernel_size=3, stride=1, padding=1)
-        self.relu2 = nn.ReLU()
-        self.pool2 = nn.MaxPool2d(2)
-
-        self.con3d = nn.Conv2d(64, 128, kernel_size=3, stride=1, padding=1)
-        self.relu3 = nn.ReLU()
-        self.pool3 = nn.MaxPool2d(2)
-
-        self.flatten = nn.Flatten()
-        self.fc1 = nn.Linear(86528, 512)  # Adjust this number to match your original
-        self.relu_fc = nn.ReLU()
-        self.fc2 = nn.Linear(512, 256)
-        self.relu_fc2 = nn.ReLU()
-        self.output = nn.Linear(256, 4)
-
-    def forward(self, x):
-        x = self.pool1(self.relu1(self.con1d(x)))
-        x = self.pool2(self.relu2(self.con2d(x)))
-        x = self.pool3(self.relu3(self.con3d(x)))
-        x = self.flatten(x)
-        x = self.relu_fc(self.fc1(x))
-        x = self.relu_fc2(self.fc2(x))
-        return self.output(x)
-
-# 🧬 Glioma Stage Prediction Model (MATCHES `glioma_stages.pth`)
 class GliomaStageModel(nn.Module):
     def __init__(self):
         super(GliomaStageModel, self).__init__()
-        self.fc1 = nn.Linear(9, 128)
+        self.fc1 = nn.Linear(9, 100)
         self.relu1 = nn.ReLU()
-        self.fc2 = nn.Linear(128, 64)
+        self.fc2 = nn.Linear(100, 50)
         self.relu2 = nn.ReLU()
-        self.fc3 = nn.Linear(64, 32)
+        self.fc3 = nn.Linear(50, 30)
         self.relu3 = nn.ReLU()
-        self.out = nn.Linear(32, 4)
+        self.out = nn.Linear(30, 2)  # Only 2 classes in this model
 
     def forward(self, x):
         x = self.relu1(self.fc1(x))