Fix Convnet test

bindings/python/examples/CifarConvNet/CifarConvNet.py

@@ -126,7 +126,7 @@ def train_and_evaluate(reader_train, reader_test, max_epochs):
     # Set learning parameters
     lr_per_minibatch       = learning_rate_schedule([0.01]*10 + [0.003]*10 + [0.001], epoch_size, UnitType.minibatch)
     momentum_time_constant = momentum_as_time_constant_schedule(-minibatch_size/np.log(0.9))
-    l2_reg_weight          = 0.03
+    l2_reg_weight          = 0.0001
 
     # trainer object
     learner     = momentum_sgd(z.parameters, 

bindings/python/examples/test/cifar_convnet_test.py

@@ -44,7 +44,7 @@ def test_cifar_resnet_error(device_id):
     reader_test  = create_reader(os.path.join(base_path, 'test_map.txt'), os.path.join(base_path, 'CIFAR-10_mean.xml'), False)
 
     test_error = train_and_evaluate(reader_train, reader_test, max_epochs=5)
-    expected_test_error = 0.462
+    expected_test_error = 0.463
 
     assert np.allclose(test_error, expected_test_error,
                        atol=TOLERANCE_ABSOLUTE)

bindings/python/examples/test/cifar_resnet_test.py

@@ -44,7 +44,7 @@ def test_cifar_resnet_error(device_id):
     reader_test  = create_reader(os.path.join(base_path, 'test_map.txt'), os.path.join(base_path, 'CIFAR-10_mean.xml'), False)
 
     test_error = train_and_evaluate(reader_train, reader_test, max_epochs=5)
-    expected_test_error = 0.36
+    expected_test_error = 0.282
 
     assert np.allclose(test_error, expected_test_error,
                        atol=TOLERANCE_ABSOLUTE)