fix(mge/test): fix tolerance

GitOrigin-RevId: 58c029b394edc17e1d6b1abb261cd76d58c6ab4f

python_module/test/integration/test_correctness.py

@@ -63,7 +63,10 @@ def train(data, label, net, opt):
 
 def update_model(model_path):
     """
-    Update the dumped model with test cases for new reference values
+    Update the dumped model with test cases for new reference values.
+
+    The model with pre-trained weights is trained for one iter with the test data attached.
+    The loss and updated net state dict is dumped.
     """
     net = MnistNet(has_bn=True)
     checkpoint = mge.load(model_path)
@@ -89,9 +92,6 @@ def run_test(model_path, use_jit, use_symbolic):
     """
     Load the model with test cases and run the training for one iter.
     The loss and updated weights are compared with reference value to verify the correctness.
-    The model with pre-trained weights is trained for one iter and the net state dict is dumped.
-    The test cases is appended to the model file. The reference result is obtained
-    by running the train for one iter. 
     
     Dump a new file with updated result by calling update_model 
     if you think the test fails due to numerical rounding errors instead of bugs. 
@@ -109,7 +109,7 @@ def run_test(model_path, use_jit, use_symbolic):
     data.set_value(checkpoint["data"])
     label.set_value(checkpoint["label"])
 
-    max_err = 0.0
+    max_err = 1e-1
 
     train_func = train
     if use_jit: