class_docstr: CDSSM Model implementation.
  
  Learning Semantic Representations Using Convolutional Neural Networks
  for Web Search. (2014a)
  A Latent Semantic Model with Convolutional-Pooling Structure for
  Information Retrieval. (2014b)
  
  Examples:
      >>> model = CDSSM()
      >>> model.params['optimizer'] = 'adam'
      >>> model.params['filters'] =  32
      >>> model.params['kernel_size'] = 3
      >>> model.params['conv_activation_func'] = 'relu'
      >>> model.guess_and_fill_missing_params(verbose=0)
      >>> model.build()
class_docstr_tok: ["CDSSM","Model","implementation",".","Learning","Semantic","Representations","Using","Convolutional","Neural","Networks","for","Web","Search",".","(","2014a",")","A","Latent","Semantic","Model","with","Convolutional-Pooling","Structure","for","Information","Retrieval",".","(","2014b",")","Examples",":",">",">",">","model","=","CDSSM","(",")",">",">",">","model.params","[","'optimizer","'","]","=","'adam'",">",">",">","model.params","[","'filters","'","]","=","32",">",">",">","model.params","[","'kernel_size","'","]","=","3",">",">",">","model.params","[","'conv_activation_func","'","]","=","'relu'",">",">",">","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."""
      # set :attr:`with_multi_layer_perceptron` to False to support
      # user-defined variable dense layer units
      params = super().get_default_params(
          with_multi_layer_perceptron=True
      )
      params.add(
          Param(
              name="filters",
              value=32,
              desc="Number of filters in the 1D convolution " "layer.",
          )
      )
      params.add(
          Param(
              name="kernel_size",
              value=3,
              desc="Number of kernel size in the 1D "
              "convolution layer.",
          )
      )
      params.add(
          Param(
              name="strides",
              value=1,
              desc="Strides in the 1D convolution layer.",
          )
      )
      params.add(
          Param(
              name="padding",
              value="same",
              desc="The padding mode in the convolution "
              "layer. It should be one of `same`, "
              "`valid`, "
              "and `causal`.",
          )
      )
      params.add(
          Param(
              name="conv_activation_func",
              value="relu",
              desc="Activation function in the convolution" " layer.",
          )
      )
      params.add(Param(name="w_initializer", value="glorot_normal"))
      params.add(Param(name="b_initializer", value="zeros"))
      params.add(
          Param(
              name="dropout_rate", value=0.3, desc="The dropout rate."
          )
      )
      return params
  
file_path: MatchZoo/matchzoo/models/cdssm.py
imports: import typing
  import keras
  from keras.models import Model
  from matchzoo.engine.base_model import BaseModel
  from matchzoo.engine.param import Param
  from matchzoo.engine.param_table import ParamTable
  from matchzoo import preprocessors
  from matchzoo.utils import TensorType
label_desc: Use image node_id 1 for calling the CDSSM obj's underlying member method code with example usage: obj.get_default_params(cls) and returns: params