Update gears.py

gears.py

@@ -5,18 +5,15 @@ import numpy as np
 
 
 def load_tensor():
-    coeffs = [None,None]
-    coeffs[0] = torch.load('tensor1.pt')
-    coeffs[1] = torch.load('tensor2.pt')
+    coeffs = torch.load('tensor.pt')
     return coeffs
 
 
-
 def calc_preds(coeffs, indeps):
     layers,consts = coeffs
     n = len(layers)
     res = indeps
     for i,l in enumerate(layers):
-        res = res@l + consts[i]
+        res = res @ l + consts[i]
         if i!=n-1: res = F.relu(res)
     return torch.sigmoid(res)