code: def transform_linear_predictor(
      model, linear_predictor: xr.DataArray, posterior: xr.DataArray
  ) -> xr.DataArray:  # pylint: disable = unused-variable
      response_name = get_aliased_name(
          model.response_component.response_term
      )
      response_levels_dim = response_name + "_reduced_dim"
      linear_predictor = linear_predictor.pad(
          {response_levels_dim: (1, 0)}, constant_values=0
      )
      return linear_predictor
  
imports: import numpy
  import pytensor.tensor
  import xarray
  from bambi.families.family import Family
  from bambi.transformations import transformations_namespace
  from bambi.utils import extract_argument_names, get_aliased_name
label_desc: Use image node_id 1 for calling the Multinomial obj's underlying member method code with example usage: obj.transform_linear_predictor(model, linear_predictor, posterior) and returns: linear_predictor