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","."]
code: def output_shape(self):
      shape = self.get_output_shape_for(self.input_shapes)
      if any(isinstance(s, T.Variable) for s in shape):
          raise ValueError(
              "%s returned a symbolic output shape from its "
              "get_output_shape_for() method: %r. This is not "
              "allowed; shapes must be tuples of integers for "
              "fixed-size dimensions and Nones for variable "
              "dimensions." % (self.__class__.__name__, shape)
          )
      return shape
  
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 2 for calling the MergeLayer obj's underlying member method code with example usage: obj.output_shape() and returns: shape