class_docstr: Encapsulate Bean Machine specific logic.
docstr: Convert posterior_predictive samples to xarray.
code: def posterior_predictive_to_xarray(self):
      """Convert posterior_predictive samples to xarray."""
      data = {
          k: v.detach().cpu().numpy()
          for k, v in self.posterior_predictive.items()
      }
      return dict_to_dataset(
          data, library=self.beanm, coords=self.coords, dims=self.dims
      )
  
file_path: arviz/arviz/data/io_beanmachine.py
imports: from .inference_data import InferenceData
  from .base import dict_to_dataset, requires
label_desc: Use image node_id 3 for calling the BMConverter obj's underlying member method code with example usage: obj.posterior_predictive_to_xarray() and returns: dict_to_dataset