def method(model):
if tensorflow.keras.backend.image_data_format() == "channels_first":
input_shape = (1, 28, 28)
else:
input_shape = (28, 28, 1)
model = tensorflow.keras.models.Sequential([
tensorflow.keras.layers.Dense(10, input_shape=input_shape),
tensorflow.keras.layers.ReLU(),
])
return DeepLIFT(model)
def method(model):
return DeepLIFT(model)