class_docstr: DIIN model.
  
  Examples:
      >>> model = DIIN()
      >>> model.guess_and_fill_missing_params()
      >>> model.params['embedding_input_dim'] = 10000
      >>> model.params['embedding_output_dim'] = 300
      >>> model.params['embedding_trainable'] = True
      >>> model.params['optimizer'] = 'adam'
      >>> model.params['dropout_initial_keep_rate'] = 1.0
      >>> model.params['dropout_decay_interval'] = 10000
      >>> model.params['dropout_decay_rate'] = 0.977
      >>> model.params['char_embedding_input_dim'] = 100
      >>> model.params['char_embedding_output_dim'] = 8
      >>> model.params['char_conv_filters'] = 100
      >>> model.params['char_conv_kernel_size'] = 5
      >>> model.params['first_scale_down_ratio'] = 0.3
      >>> model.params['nb_dense_blocks'] = 3
      >>> model.params['layers_per_dense_block'] = 8
      >>> model.params['growth_rate'] = 20
      >>> model.params['transition_scale_down_ratio'] = 0.5
      >>> model.build()
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docstr: Guess and fill missing parameters in :attr:'params'.
  
  Use this method to automatically fill-in hyper parameters.
  This involves some guessing so the parameter it fills could be
  wrong. For example, the default task is 'Ranking', and if we do not
  set it to 'Classification' manually for data packs prepared for
  classification, then the shape of the model output and the data will
  mismatch.
  
  :param verbose: Verbosity.
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code: def guess_and_fill_missing_params(self, verbose: int = 1):
      """
      Guess and fill missing parameters in :attr:'params'.
  
      Use this method to automatically fill-in hyper parameters.
      This involves some guessing so the parameter it fills could be
      wrong. For example, the default task is 'Ranking', and if we do not
      set it to 'Classification' manually for data packs prepared for
      classification, then the shape of the model output and the data will
      mismatch.
  
      :param verbose: Verbosity.
      """
      self._params.get("input_shapes").set_default(
          [(32,), (32,), (32, 16), (32, 16), (32,), (32,)], verbose
      )
      super().guess_and_fill_missing_params(verbose)
  
imports: import typing
  import keras
  import keras.backend
  import tensorflow
  from matchzoo import preprocessors
  from matchzoo.contrib.layers import DecayingDropoutLayer
  from matchzoo.contrib.layers import EncodingLayer
  from matchzoo.engine import hyper_spaces
  from matchzoo.engine.base_model import BaseModel
  from matchzoo.engine.param import Param
  from matchzoo.engine.param_table import ParamTable
label_desc: Use image node_id 3 for calling the DIIN obj's underlying member method code with example usage: obj.guess_and_fill_missing_params(verbose) without return types