Formatting

Author: Giuseppe5

tests/brevitas/graph/test_calibration.py

@@ -28,7 +28,9 @@
 REFERENCE_SCALES = {
     'int_quant': (0.00935234408825635910, 0.01362917013466358185),
     'fp_quant': (0.00249395845457911491, 0.00363444536924362183)}
-REFERNECE_INP = torch.tensor([[-1.8645, -0.4071, 1.1971]])
+REFERENCE_INP = torch.tensor([[-1.8645, -0.4071, 1.1971]])
+REFERENCE_WEIGHTS = torch.tensor([[1.0023, 0.0205, 1.4604], [-0.2918, -1.8218, -0.7010],
+                                  [1.4573, -0.9074, -0.2708]])
 
 
 def compute_quantile(x, q):
@@ -86,9 +88,7 @@ class TestModel(nn.Module):
         def __init__(self):
             super(TestModel, self).__init__()
             self.act = qnn.QuantReLU(act_quant=act_quant)
-            self.linear_weights = torch.tensor([[1.0023, 0.0205,
-                                                 1.4604], [-0.2918, -1.8218, -0.7010],
-                                                [1.4573, -0.9074, -0.2708]])
+            self.linear_weights = REFERENCE_WEIGHTS
             self.act_1 = qnn.QuantIdentity(act_quant=act_quant)
 
         def forward(self, x):
@@ -97,7 +97,7 @@ def forward(self, x):
             return self.act_1(o)
 
     # Reference input
-    inp = REFERNECE_INP
+    inp = REFERENCE_INP
     model = TestModel()
     model.eval()
     with torch.no_grad():