class_docstr: ArcI Model.
  
  Examples:
      >>> model = ArcI()
      >>> model.params['num_blocks'] = 1
      >>> model.params['left_filters'] = [32]
      >>> model.params['right_filters'] = [32]
      >>> model.params['left_kernel_sizes'] = [3]
      >>> model.params['right_kernel_sizes'] = [3]
      >>> model.params['left_pool_sizes'] = [2]
      >>> model.params['right_pool_sizes'] = [4]
      >>> model.params['conv_activation_func'] = 'relu'
      >>> model.params['mlp_num_layers'] = 1
      >>> model.params['mlp_num_units'] = 64
      >>> model.params['mlp_num_fan_out'] = 32
      >>> model.params['mlp_activation_func'] = 'relu'
      >>> model.params['dropout_rate'] = 0.5
      >>> model.guess_and_fill_missing_params(verbose=0)
      >>> model.build()
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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, with_multi_layer_perceptron=True
      )
      params["optimizer"] = "adam"
      params.add(
          Param(
              name="num_blocks",
              value=1,
              desc="Number of convolution blocks.",
          )
      )
      params.add(
          Param(
              name="left_filters",
              value=[32],
              desc="The filter size of each convolution "
              "blocks for the left input.",
          )
      )
      params.add(
          Param(
              name="left_kernel_sizes",
              value=[3],
              desc="The kernel size of each convolution "
              "blocks for the left input.",
          )
      )
      params.add(
          Param(
              name="right_filters",
              value=[32],
              desc="The filter size of each convolution "
              "blocks for the right input.",
          )
      )
      params.add(
          Param(
              name="right_kernel_sizes",
              value=[3],
              desc="The kernel size of each convolution "
              "blocks for the right input.",
          )
      )
      params.add(
          Param(
              name="conv_activation_func",
              value="relu",
              desc="The activation function in the "
              "convolution layer.",
          )
      )
      params.add(
          Param(
              name="left_pool_sizes",
              value=[2],
              desc="The pooling size of each convolution "
              "blocks for the left input.",
          )
      )
      params.add(
          Param(
              name="right_pool_sizes",
              value=[2],
              desc="The pooling size of each convolution "
              "blocks for the right input.",
          )
      )
      params.add(
          Param(
              name="padding",
              value="same",
              hyper_space=hyper_spaces.choice(
                  ["same", "valid", "causal"]
              ),
              desc="The padding mode in the convolution layer. It should be one"
              "of `same`, `valid`, and `causal`.",
          )
      )
      params.add(
          Param(
              "dropout_rate",
              0.0,
              hyper_space=hyper_spaces.quniform(
                  low=0.0, high=0.8, q=0.01
              ),
              desc="The dropout rate.",
          )
      )
      return params
  
file_path: MatchZoo/matchzoo/models/arci.py
imports: import typing
  import keras
  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 ArcI obj's underlying member method code with example usage: obj.get_default_params(cls) and returns: params