code: def get_attribute_prediction_model(config):
      name = config["name"]
      hparams = config["hparams"]
      if name == "dap":
          model = DAP(**hparams)
      else:
          raise Exception("{} model is not supported".format(name))
  
      return model
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from nemo.collections.tts.modules.common import ConvLSTMLinear
  from nemo.collections.tts.modules.submodules import ConvNorm, MaskedInstanceNorm1d
  from nemo.collections.tts.modules.transformer import FFTransformer
  from nemo.collections.tts.parts.utils.helpers import get_mask_from_lengths
label_desc: Use image node_id 1 for calling a global function with example usage: get_attribute_prediction_model(config) and returns: model