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 __init__(self, incomings, name=None):
      self.input_shapes = [
          incoming
          if isinstance(incoming, tuple)
          else incoming.output_shape
          for incoming in incomings
      ]
      self.input_layers = [
          None if isinstance(incoming, tuple) else incoming
          for incoming in incomings
      ]
      self.name = name
      self.params = OrderedDict()
      self.get_output_kwargs = []
  
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 1 to create a new MergeLayer object from inherited base classes: Layer with example: obj = MergeLayer(incomings, name)