class_docstr: A simple densely connected baseline model.
  
  Examples:
      >>> model = DenseBaseline()
      >>> model.params['mlp_num_layers'] = 2
      >>> model.params['mlp_num_units'] = 300
      >>> model.params['mlp_num_fan_out'] = 128
      >>> model.params['mlp_activation_func'] = 'relu'
      >>> model.guess_and_fill_missing_params(verbose=0)
      >>> model.build()
      >>> model.compile()
docstr: Model structure.
docstr_tok: ["Model","structure","."]
code: def build(self):
      """Model structure."""
      x_in = self._make_inputs()
      x = keras.layers.concatenate(x_in)
      x = self._make_multi_layer_perceptron_layer()(x)
      x_out = self._make_output_layer()(x)
      self._backend = keras.models.Model(inputs=x_in, outputs=x_out)
  
imports: import keras.layers
  from matchzoo.engine.base_model import BaseModel
  from matchzoo.engine.param_table import ParamTable
  from matchzoo.engine import hyper_spaces
label_desc: Use image node_id 2 for calling the DenseBaseline obj's underlying member method code with example usage: obj.build() without return types