code: def default_trainer_params(cls):
      p = super().default_trainer_params()
      p.scenario.model.layers = [
          Conv2DLayerParams(filters=2),
          MaxPool2DLayerParams(pool_size=IntVec2D(4, 4)),
          BiLSTMLayerParams(hidden_nodes=2),
          DropoutLayerParams(rate=0.5),
      ]
      p.gen.setup.val.batch_size = 1
      p.gen.setup.val.num_processes = 1
      p.gen.setup.train.batch_size = 1
      p.gen.setup.train.num_processes = 1
      p.epochs = 1
      p.samples_per_epoch = 2
      p.scenario.data.pre_proc.run_parallel = False
      post_init(p)
      return p
  
file_path: calamari/calamari_ocr/test/calamari_test_scenario.py
imports: from tfaip.util.tfaipargparse import post_init
  from calamari_ocr.ocr.model.layers.bilstm import BiLSTMLayerParams
  from calamari_ocr.ocr.model.layers.conv2d import Conv2DLayerParams
  from calamari_ocr.ocr.model.layers.dropout import DropoutLayerParams
  from calamari_ocr.ocr.model.layers.layer import IntVec2D
  from calamari_ocr.ocr.model.layers.pool2d import MaxPool2DLayerParams
  from calamari_ocr.ocr.scenario import CalamariScenario, CalamariEnsembleScenario
label_desc: Use image node_id 1 for calling the CalamariTestEnsembleScenario obj's underlying member method code with example usage: obj.default_trainer_params(cls) and returns: p