class_docstr: MpAttentiveMatch Layer.
  
  Reference:
  https://github.com/zhiguowang/BiMPM/blob/master/src/match_utils.py#L188-L193
  
  Examples:
      >>> import matchzoo as mz
      >>> layer = mz.contrib.layers.multi_perspective_layer.MpAttentiveMatch(
      ...     att_dim=30, mp_dim=20)
      >>> layer.compute_output_shape([(32, 10, 100), (32, 40, 100)])
      (32, 40, 20)
class_docstr_tok: ["MpAttentiveMatch","Layer",".","Reference",":","https",":","\/\/github.com\/zhiguowang\/BiMPM\/blob\/master\/src\/match_utils.py","#","L188-L193","Examples",":",">",">",">","import","matchzoo","as","mz",">",">",">","layer","=","mz.contrib.layers.multi_perspective_layer.MpAttentiveMatch","(","...","att_dim=30",",","mp_dim=20",")",">",">",">","layer.compute_output_shape","(","[","(","32",",","10",",","100",")",",","(","32",",","40",",","100",")","]",")","(","32",",","40",",","20",")"]
docstr: Compute output shape.
docstr_tok: ["Compute","output","shape","."]
code: def compute_output_shape(self, input_shape):
      """Compute output shape."""
      return input_shape[1][0], input_shape[1][1], self.mp_dim
  
imports: import tensorflow
  from keras import backend
  from keras.engine import Layer
  from matchzoo.contrib.layers.attention_layer import AttentionLayer
label_desc: Use image node_id 4 for calling the MpAttentiveMatch obj's underlying member method code with example usage: obj.compute_output_shape(input_shape) and returns: input_shape,  input_shape,  self