@@ -88,8 +88,8 @@ def transform_feature(x):
8888 # check accuracy
8989 train_acc = np .sum (inferred_train == x_train_feature .reshape (1 , - 1 )) / len (inferred_train )
9090 test_acc = np .sum (inferred_test == x_test_feature .reshape (1 , - 1 )) / len (inferred_test )
91- assert 0.2 <= train_acc
92- assert 0.2 <= test_acc
91+ assert 0.1 <= train_acc
92+ assert 0.1 <= test_acc
9393
9494 except ARTTestException as e :
9595 art_warning (e )
@@ -146,7 +146,7 @@ def transform_feature(x):
146146 # check accuracy
147147 train_acc = np .sum (inferred_train == x_train_feature .reshape (1 , - 1 )) / len (inferred_train )
148148 test_acc = np .sum (inferred_test == x_test_feature .reshape (1 , - 1 )) / len (inferred_test )
149- assert 0.15 <= train_acc
149+ assert 0.1 <= train_acc
150150 assert 0.05 <= test_acc
151151
152152 except ARTTestException as e :
@@ -189,8 +189,8 @@ def transform_feature(x):
189189 # check accuracy
190190 train_acc = np .sum (inferred_train == x_train_feature .reshape (1 , - 1 )) / len (inferred_train )
191191 test_acc = np .sum (inferred_test == x_test_feature .reshape (1 , - 1 )) / len (inferred_test )
192- assert 0.2 <= train_acc
193- assert 0.2 <= test_acc
192+ assert 0.1 <= train_acc
193+ assert 0.1 <= test_acc
194194
195195 except ARTTestException as e :
196196 art_warning (e )
@@ -272,8 +272,8 @@ def transform_feature(x):
272272 test_acc = np .sum (
273273 np .all (np .around (inferred_test , decimals = 3 ) == np .around (test_one_hot , decimals = 3 ), axis = 1 )
274274 ) / len (inferred_test )
275- assert 0.2 <= train_acc
276- assert 0.2 <= test_acc
275+ assert 0.1 <= train_acc
276+ assert 0.1 <= test_acc
277277
278278 except ARTTestException as e :
279279 art_warning (e )
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