class_docstr: Layer that compute attention for BiMPM model.
  
  For detailed information, see Bilateral Multi-Perspective Matching for
  Natural Language Sentences, section 3.2.
  
  Reference:
  https://github.com/zhiguowang/BiMPM/blob/master/src/layer_utils.py#L145-L196
  
  Examples:
      >>> import matchzoo as mz
      >>> layer = mz.contrib.layers.AttentionLayer(att_dim=50)
      >>> layer.compute_output_shape([(32, 10, 100), (32, 40, 100)])
      (32, 10, 40)
class_docstr_tok: ["Layer","that","compute","attention","for","BiMPM","model",".","For","detailed","information",",","see","Bilateral","Multi-Perspective","Matching","for","Natural","Language","Sentences",",","section","3.2",".","Reference",":","https",":","\/\/github.com\/zhiguowang\/BiMPM\/blob\/master\/src\/layer_utils.py","#","L145-L196","Examples",":",">",">",">","import","matchzoo","as","mz",">",">",">","layer","=","mz.contrib.layers.AttentionLayer","(","att_dim=50",")",">",">",">","layer.compute_output_shape","(","[","(","32",",","10",",","100",")",",","(","32",",","40",",","100",")","]",")","(","32",",","10",",","40",")"]
docstr: Get the attention type.
docstr_tok: ["Get","the","attention","type","."]
code: def att_type(self):
      """Get the attention type."""
      return self._att_type
  
file_path: MatchZoo/matchzoo/contrib/layers/attention_layer.py
imports: import tensorflow
  from keras import backend
  from keras.engine import Layer
label_desc: Use image node_id 3 for calling the AttentionLayer obj's underlying member method code with example usage: obj.att_type() and returns: self