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: Computes the output shape of this layer, given a list of input shapes.
  
  Parameters
  ----------
  input_shape : list of tuple
      A list of tuples, with each tuple representing the shape of one of
      the inputs (in the correct order). These tuples should have as many
      elements as there are input dimensions, and the elements should be
      integers or `None`.
  
  Returns
  -------
  tuple
      A tuple representing the shape of the output of this layer. The
      tuple has as many elements as there are output dimensions, and the
      elements are all either integers or `None`.
  
  Notes
  -----
  This method must be overridden when implementing a new
  :class:`Layer` class with multiple inputs. By default it raises
  `NotImplementedError`.
docstr_tok: ["Computes","the","output","shape","of","this","layer",",","given","a","list","of","input","shapes",".","Parameters","--","--","--","--","--","input_shape",":","list","of","tuple","A","list","of","tuples",",","with","each","tuple","representing","the","shape","of","one","of","the","inputs","(","in","the","correct","order",")",".","These","tuples","should","have","as","many","elements","as","there","are","input","dimensions",",","and","the","elements","should","be","integers","or","`","None","`",".","Returns","--","--","--","-","tuple","A","tuple","representing","the","shape","of","the","output","of","this","layer",".","The","tuple","has","as","many","elements","as","there","are","output","dimensions",",","and","the","elements","are","all","either","integers","or","`","None","`",".","Notes","--","--","-","This","method","must","be","overridden","when","implementing","a","new",":","class",":","`","Layer","`","class","with","multiple","inputs",".","By","default","it","raises","`","NotImplementedError","`","."]
code: def get_output_shape_for(self, input_shapes):
      """
      Computes the output shape of this layer, given a list of input shapes.
  
      Parameters
      ----------
      input_shape : list of tuple
          A list of tuples, with each tuple representing the shape of one of
          the inputs (in the correct order). These tuples should have as many
          elements as there are input dimensions, and the elements should be
          integers or `None`.
  
      Returns
      -------
      tuple
          A tuple representing the shape of the output of this layer. The
          tuple has as many elements as there are output dimensions, and the
          elements are all either integers or `None`.
  
      Notes
      -----
      This method must 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 3 for calling the MergeLayer obj's underlying member method code with example usage: obj.get_output_shape_for(input_shapes) without return types