def get_activation_by_name(activation_name, activation_id=None):
""" Convert to a bigdl activation layer
given the name of the activation as a string """
import bigdl.nn.layer as BLayer
activation = None
activation_name = activation_name.lower()
if activation_name == "tanh":
activation = BLayer.Tanh()
elif activation_name == "sigmoid":
activation = BLayer.Sigmoid()
elif activation_name == "hard_sigmoid":
activation = BLayer.HardSigmoid()
elif activation_name == "relu":
activation = BLayer.ReLU()
elif activation_name == "softmax":
activation = BLayer.SoftMax()
elif activation_name == "softplus":
activation = BLayer.SoftPlus(beta=1.0)
elif activation_name == "softsign":
activation = BLayer.SoftSign()
elif activation_name == "linear":
activation = BLayer.Identity()
else:
raise Exception("Unsupported activation type: %s" % activation_name)
if not activation_id:
activation.set_name(activation_id)
return activation
def create_inputlayer(self, klayer, kclyer):
return BLayer.Identity()
def _to_tensor(self):
identity = zlayers.KerasLayerWrapper(blayer.Identity())
return identity(self.model_inputs[0].zvalue)
