I just want to know if is it possible to use tf.estimator.DNNClassifier with multiple different activation functions. I mean, could I use a DNNClassifier estimator which use different activation functions for different layers?
For example, if I have a three layers model, could I use for the first layer a sigmoid function, for the second one a ReLu function and finally for the last one a tanh function?
I would like to know if it isn't possible to do it with DNNClassifier how can I do it by a easy way.
