add comment and param check

example/mnist_demo/lenet5_mnist_coverage.py

@@ -67,7 +67,7 @@ def test_lenet_mnist_coverage():
         test_labels.append(labels)
     test_images = np.concatenate(test_images, axis=0)
     test_labels = np.concatenate(test_labels, axis=0)
-    model_fuzz_test.test_adequacy_coverage_calculate(test_images)
+    model_fuzz_test.calculate_coverage(test_images)
     LOGGER.info(TAG, 'KMNC of this test is : %s', model_fuzz_test.get_kmnc())
     LOGGER.info(TAG, 'NBC of this test is : %s', model_fuzz_test.get_nbc())
     LOGGER.info(TAG, 'SNAC of this test is : %s', model_fuzz_test.get_snac())
@@ -76,14 +76,13 @@ def test_lenet_mnist_coverage():
     loss = SoftmaxCrossEntropyWithLogits(is_grad=False, sparse=True)
     attack = FastGradientSignMethod(net, eps=0.3, loss_fn=loss)
     adv_data = attack.batch_generate(test_images, test_labels, batch_size=32)
-    model_fuzz_test.test_adequacy_coverage_calculate(adv_data,
-                                                     bias_coefficient=0.5)
-    LOGGER.info(TAG, 'KMNC of this test is : %s', model_fuzz_test.get_kmnc())
-    LOGGER.info(TAG, 'NBC of this test is : %s', model_fuzz_test.get_nbc())
-    LOGGER.info(TAG, 'SNAC of this test is : %s', model_fuzz_test.get_snac())
+    model_fuzz_test.calculate_coverage(adv_data, bias_coefficient=0.5)
+    LOGGER.info(TAG, 'KMNC of this adv data is : %s', model_fuzz_test.get_kmnc())
+    LOGGER.info(TAG, 'NBC of this adv data is : %s', model_fuzz_test.get_nbc())
+    LOGGER.info(TAG, 'SNAC of this adv data is : %s', model_fuzz_test.get_snac())
 
 
 if __name__ == '__main__':
     # device_target can be "CPU", "GPU" or "Ascend"
-    context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
+    context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
     test_lenet_mnist_coverage()

example/mnist_demo/lenet5_mnist_fuzzing.py

@@ -87,9 +87,9 @@ def test_lenet_mnist_fuzzing():
     LOGGER.info(TAG, 'KMNC of this test is : %s',
                 model_coverage_test.get_kmnc())
 
-    model_fuzz_test = Fuzzer(model, train_images, 1000, 10)
+    model_fuzz_test = Fuzzer(model, train_images, 10, 1000)
     _, _, _, _, metrics = model_fuzz_test.fuzzing(mutate_config, initial_seeds,
-                                                  eval_metric=True)
+                                                  eval_metrics='auto')
     if metrics:
         for key in metrics:
             LOGGER.info(TAG, key + ': %s', metrics[key])
@@ -97,5 +97,5 @@ def test_lenet_mnist_fuzzing():
 
 if __name__ == '__main__':
     # device_target can be "CPU", "GPU" or "Ascend"
-    context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
+    context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
     test_lenet_mnist_fuzzing()

tests/ut/python/fuzzing/test_fuzzer.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """
-Model-fuzz coverage test.
+Model-fuzzer test.
 """
 import numpy as np
 import pytest
@@ -121,7 +121,7 @@ def test_fuzzing_ascend():
     LOGGER.info(TAG, 'KMNC of this test is : %s',
                 model_coverage_test.get_kmnc())
 
-    model_fuzz_test = Fuzzer(model, train_images, 1000, 10)
+    model_fuzz_test = Fuzzer(model, train_images, 10, 1000)
     _, _, _, _, metrics = model_fuzz_test.fuzzing(mutate_config, initial_seeds)
     print(metrics)
 
@@ -167,6 +167,6 @@ def test_fuzzing_cpu():
     LOGGER.info(TAG, 'KMNC of this test is : %s',
                 model_coverage_test.get_kmnc())
 
-    model_fuzz_test = Fuzzer(model, train_images, 1000, 10)
+    model_fuzz_test = Fuzzer(model, train_images, 10, 1000)
     _, _, _, _, metrics = model_fuzz_test.fuzzing(mutate_config, initial_seeds)
     print(metrics)