class_docstr: ANMM Model.
  
  Examples:
      >>> model = ANMM()
      >>> model.guess_and_fill_missing_params(verbose=0)
      >>> model.build()
class_docstr_tok: ["ANMM","Model",".","Examples",":",">",">",">","model","=","ANMM","(",")",">",">",">","model.guess_and_fill_missing_params","(","verbose=0",")",">",">",">","model.build","(",")"]
docstr: :return: model default parameters.
docstr_tok: [":","return",":","model","default","parameters","."]
code: def get_default_params(cls) -> ParamTable:
      """:return: model default parameters."""
      params = super().get_default_params(with_embedding=True)
      params.add(
          Param(
              name="dropout_rate",
              value=0.1,
              desc="The dropout rate.",
              hyper_space=hyper_spaces.quniform(0, 1, 0.05),
          )
      )
      params.add(
          Param(
              name="num_layers",
              value=2,
              desc="Number of hidden layers in the MLP " "layer.",
          )
      )
      params.add(
          Param(
              name="hidden_sizes",
              value=[30, 30],
              desc="Number of hidden size for each hidden" " layer",
          )
      )
      return params
  
file_path: MatchZoo/matchzoo/models/anmm.py
imports: import keras
  from keras.activations import softmax
  from keras.initializers import RandomUniform
  from matchzoo.engine.base_model import BaseModel
  from matchzoo.engine.param import Param
  from matchzoo.engine.param_table import ParamTable
  from matchzoo.engine import hyper_spaces
label_desc: Use image node_id 1 for calling the ANMM obj's underlying member method code with example usage: obj.get_default_params(cls) and returns: params