class_docstr: HBMP model.
  
  Examples:
      >>> model = HBMP()
      >>> model.guess_and_fill_missing_params(verbose=0)
      >>> model.params['embedding_input_dim'] = 200
      >>> model.params['embedding_output_dim'] = 100
      >>> model.params['embedding_trainable'] = True
      >>> model.params['alpha'] = 0.1
      >>> model.params['mlp_num_layers'] = 3
      >>> model.params['mlp_num_units'] = [10, 10]
      >>> model.params['lstm_num_units'] = 5
      >>> model.params['dropout_rate'] = 0.1
      >>> model.build()
code: def _classifier(
      self,
      input_: typing.Any,
      mlp_num_layers: int,
      mlp_num_units: list,
      drop_rate: float,
      leaky_relu_alpah: float,
  ) -> typing.Any:
      for i in range(mlp_num_layers - 1):
          input_ = keras.layers.Dropout(rate=drop_rate)(input_)
          input_ = keras.layers.Dense(mlp_num_units[i])(input_)
          input_ = keras.layers.LeakyReLU(alpha=leaky_relu_alpah)(
              input_
          )
  
      return input_
  
file_path: MatchZoo/matchzoo/contrib/models/hbmp.py
imports: import keras
  import typing
  from matchzoo.engine import hyper_spaces
  from matchzoo.engine.param_table import ParamTable
  from matchzoo.engine.param import Param
  from matchzoo.engine.base_model import BaseModel
label_desc: Use image node_id 3 for calling the HBMP obj's underlying member method code with example usage: obj._classifier(input_, mlp_num_layers, mlp_num_units, drop_rate, leaky_relu_alpah) and returns: input_