added new fixed code

model.py

@@ -0,0 +1,31 @@
+import torch.nn as nn
+
+INPUT_KERNEL = 15
+SIZE = 32
+
+
+class CavemanEnhancer(nn.Module):
+    def __init__(self, freq_bins=513):
+        super().__init__()
+        self.net = nn.Sequential(
+            nn.Conv2d(
+                in_channels=1,
+                out_channels=SIZE,
+                kernel_size=INPUT_KERNEL,
+                padding=INPUT_KERNEL // 2,
+            ),
+            nn.ReLU(),
+            nn.Conv2d(SIZE, SIZE, kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.Conv2d(SIZE, SIZE, kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.Conv2d(SIZE, SIZE, kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.Conv2d(SIZE, SIZE, kernel_size=3, padding=1),
+            nn.ReLU(),
+            nn.Conv2d(SIZE, 1, kernel_size=3, padding=1),
+        )
+
+    def forward(self, x):
+        # x: (batch, freq_bins)
+        return self.net(x)