736ba6c6873290fdae110395040f76ba7ab0ff19,tests/test_net_transformer.py,,test_net_transformer,#,3
Before Change
def test_net_transformer():
model_a = Sequential()
model_a.add(Conv2D(32, (3, 3), activation="relu", input_shape=(28, 28, 1)))
model_a.add(Conv2D(32, (3, 3), activation="relu"))
model_a.add(MaxPooling2D(pool_size=(2, 2)))
model_a.add(Dropout(0.25))
After Change
//print(model.summary())
models = net_transfromer(model)
//print(models[5].summary())
for new_model in models:
output2 = new_model.predict_on_batch(random_input)
assert np.sum(output1.flatten() - output2.flatten()) < 1e-4
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 4
Instances
Project Name: jhfjhfj1/autokeras
Commit Name: 736ba6c6873290fdae110395040f76ba7ab0ff19
Time: 2017-12-17
Author: wangtaoo665@gmail.com
File Name: tests/test_net_transformer.py
Class Name:
Method Name: test_net_transformer
Project Name: deepchem/deepchem
Commit Name: de7f5863338af5e1f92257cb29a6ca9a1c52c473
Time: 2019-07-10
Author: peastman@stanford.edu
File Name: examples/low_data/toxcast_maml.py
Class Name:
Method Name: compute_scores