class_docstr: lasagne.layers.NonlinearityLayer(incoming,
  nonlinearity=lasagne.nonlinearities.rectify, **kwargs)
  
  A layer that just applies a nonlinearity.
  
  Parameters
  ----------
  incoming : a :class:`Layer` instance or a tuple
      The layer feeding into this layer, or the expected input shape
  
  nonlinearity : callable or None
      The nonlinearity that is applied to the layer activations. If None
      is provided, the layer will be linear.
code: def get_output_for(self, input, **kwargs):
      return self.nonlinearity(input)
  
imports: import theano
  import theano.tensor
  import numpy
  from ..None import init
  from ..None import nonlinearities
  from ..utils import as_tuple, floatX, int_types
  from ..random import get_rng
  from .base import Layer, MergeLayer
  from theano.sandbox.rng_mrg import MRG_RandomStreams
label_desc: Use image node_id 2 for calling the NonlinearityLayer obj's underlying member method code with example usage: obj.get_output_for(input) and returns: self