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: :return: Default preprocessor.
docstr_tok: [":","return",":","Default","preprocessor","."]
code: def get_default_preprocessor(cls):
      """:return: Default preprocessor."""
      return preprocessors.DIINPreprocessor()
  
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 2 for calling the DIIN obj's underlying member method code with example usage: obj.get_default_preprocessor(cls) and returns: preprocessors