Error when cloning amodel with custom activation function

Hello,

While I was trying to clone a model I faced the following error:

Traceback (most recent call last):

File “<ipython-input-69-598bf1638a5a>”, line 10, in <module> model_RMSE = clone_model(model)

File “/usr/local/lib/python3.5/dist-packages/keras/models.py”, line 1523, in clone_model if layer not in layer_map:

File “/usr/local/lib/python3.5/dist-packages/keras/models.py”, line 1378, in _clone_functional_model merge_config = self.layers[0].get_config()

File “/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py”, line 1252, in from_config # Returns

File “/usr/local/lib/python3.5/dist-packages/keras/legacy/interfaces.py”, line 87, in wrapper return func(*args, **kwargs)

File “/usr/local/lib/python3.5/dist-packages/keras/layers/core.py”, line 808, in init super(Dense, self).init(**kwargs)

File “/usr/local/lib/python3.5/dist-packages/keras/activations.py”, line 95, in get if identifier is None:

File “/usr/local/lib/python3.5/dist-packages/keras/activations.py”, line 87, in deserialize def deserialize(name, custom_objects=None):

File “/usr/local/lib/python3.5/dist-packages/keras/utils/generic_utils.py”, line 159, in deserialize_keras_object if fn is None:

ValueError: Unknown activation function:exp Here is a minimal reproducible example:

from keras.models import Model,clone_model
from keras.layers import Input, Dense
from keras.optimizers import Adam
from keras import backend as K

inputs = Input(name='input1', shape=(1,))
model = Dense(15, activation='relu') (inputs)
outputs = Dense(1, activation=K.exp) (model)
model = Model(inputs=inputs, outputs=outputs)
model.compile(loss='poisson',optimizer=Adam(lr=5e-3))
model_clone = clone_model(model)

When replacing outputs = Dense(1, activation=K.exp) (model) to outputs = Dense(1, activation=None) (model) error is vanishing. Any idea how to solve this problem?

[FedericoMuciaccia]

I still have this bug

x = keras.layers.Activation(my_custom_activation_function)(x) is not working. I have to use x = keras.layers.Lambda(my_custom_activation_function)(x) instead

why this strange behaviour?

[blakedewey]

This is a little more pressing now, as clone_model is used in multi_gpu_model when cpu_relocation is True.