class_docstr: This class represents a layer that aggregates input from multiple layers.
  It should be subclassed when implementing new types of layers that obtain
  their input from multiple layers.
  
  Parameters
  ----------
  incomings : a list of :class:`Layer` instances or tuples
      The layers feeding into this layer, or expected input shapes.
  name : a string or None
      An optional name to attach to this layer.
class_docstr_tok: ["This","class","represents","a","layer","that","aggregates","input","from","multiple","layers",".","It","should","be","subclassed","when","implementing","new","types","of","layers","that","obtain","their","input","from","multiple","layers",".","Parameters","--","--","--","--","--","incomings",":","a","list","of",":","class",":","`","Layer","`","instances","or","tuples","The","layers","feeding","into","this","layer",",","or","expected","input","shapes",".","name",":","a","string","or","None","An","optional","name","to","attach","to","this","layer","."]
docstr: Propagates the given inputs through this layer (and only this layer).
  
  Parameters
  ----------
  inputs : list of Theano expressions
      The Theano expressions to propagate through this layer.
  
  Returns
  -------
  Theano expressions
      The output of this layer given the inputs to this layer.
  
  Notes
  -----
  This is called by the base :meth:`lasagne.layers.get_output()`
  to propagate data through a network.
  
  This method should be overridden when implementing a new
  :class:`Layer` class with multiple inputs. By default it raises
  `NotImplementedError`.
docstr_tok: ["Propagates","the","given","inputs","through","this","layer","(","and","only","this","layer",")",".","Parameters","--","--","--","--","--","inputs",":","list","of","Theano","expressions","The","Theano","expressions","to","propagate","through","this","layer",".","Returns","--","--","--","-","Theano","expressions","The","output","of","this","layer","given","the","inputs","to","this","layer",".","Notes","--","--","-","This","is","called","by","the","base",":","meth",":","`","lasagne.layers.get_output","(",")","`","to","propagate","data","through","a","network",".","This","method","should","be","overridden","when","implementing","a","new",":","class",":","`","Layer","`","class","with","multiple","inputs",".","By","default","it","raises","`","NotImplementedError","`","."]
code: def get_output_for(self, inputs, **kwargs):
      """
      Propagates the given inputs through this layer (and only this layer).
  
      Parameters
      ----------
      inputs : list of Theano expressions
          The Theano expressions to propagate through this layer.
  
      Returns
      -------
      Theano expressions
          The output of this layer given the inputs to this layer.
  
      Notes
      -----
      This is called by the base :meth:`lasagne.layers.get_output()`
      to propagate data through a network.
  
      This method should be overridden when implementing a new
      :class:`Layer` class with multiple inputs. By default it raises
      `NotImplementedError`.
      """
      raise NotImplementedError
  
file_path: Lasagne/lasagne/layers/base.py
imports: from collections import OrderedDict
  import theano.tensor
  from ..None import utils
label_desc: Use image node_id 4 for calling the MergeLayer obj's underlying member method code with example usage: obj.get_output_for(inputs) without return types