class_docstr: MatchPyramid Model.
  
  Examples:
      >>> model = MatchPyramid()
      >>> model.params['embedding_output_dim'] = 300
      >>> model.params['num_blocks'] = 2
      >>> model.params['kernel_count'] = [16, 32]
      >>> model.params['kernel_size'] = [[3, 3], [3, 3]]
      >>> model.params['dpool_size'] = [3, 10]
      >>> model.guess_and_fill_missing_params(verbose=0)
      >>> model.build()
code: def _conv_block(
      cls,
      x,
      kernel_count: int,
      kernel_size: int,
      padding: str,
      activation: str,
  ) -> typing.Any:
      output = keras.layers.Conv2D(
          kernel_count,
          kernel_size,
          padding=padding,
          activation=activation,
      )(x)
      return output
  
file_path: MatchZoo/matchzoo/models/match_pyramid.py
imports: import typing
  import keras
  import matchzoo
  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 3 for calling the MatchPyramid obj's underlying member method code with example usage: obj._conv_block(cls, x, kernel_count, kernel_size, padding, activation) and returns: output