code: def from_dict(
      posterior=None,
      *,
      posterior_predictive=None,
      predictions=None,
      sample_stats=None,
      log_likelihood=None,
      prior=None,
      prior_predictive=None,
      sample_stats_prior=None,
      observed_data=None,
      constant_data=None,
      predictions_constant_data=None,
      warmup_posterior=None,
      warmup_posterior_predictive=None,
      warmup_predictions=None,
      warmup_log_likelihood=None,
      warmup_sample_stats=None,
      save_warmup=None,
      index_origin: Optional[int] = None,
      coords=None,
      dims=None,
      pred_dims=None,
      pred_coords=None,
      attrs=None,
      **kwargs,
  ):
      """Convert Dictionary data into an InferenceData object.
  
      For a usage example read the
      :ref:`Creating InferenceData section on from_dict <creating_InferenceData>`
  
      Parameters
      ----------
      posterior : dict, optional
      posterior_predictive : dict, optional
      predictions: dict, optional
      sample_stats : dict, optional
      log_likelihood : dict, optional
          For stats functions, log likelihood data should be stored here.
      prior : dict, optional
      prior_predictive : dict, optional
      observed_data : dict, optional
      constant_data : dict, optional
      predictions_constant_data: dict, optional
      warmup_posterior : dict, optional
      warmup_posterior_predictive : dict, optional
      warmup_predictions : dict, optional
      warmup_log_likelihood : dict, optional
      warmup_sample_stats : dict, optional
      save_warmup : bool, optional
          Save warmup iterations InferenceData object. If not defined, use default
          defined by the rcParams.
      index_origin : int, optional
      coords : dict of {str : list}, optional
          A dictionary containing the values that are used as index. The key
          is the name of the dimension, the values are the index values.
      dims : dict of {str : list of str}, optional
          A mapping from variables to a list of coordinate names for the variable.
      pred_dims : dict of {str : list of str}, optional
          A mapping from variables to a list of coordinate names for predictions.
      pred_coords : dict of {str : list}, optional
          A mapping from variables to a list of coordinate values for predictions.
      attrs : dict, optional
          A dictionary containing attributes for different groups.
      kwargs : dict, optional
          A dictionary containing group attrs. Accepted kwargs are:
  
          - posterior_attrs, posterior_warmup_attrs : attrs for posterior group
          - sample_stats_attrs, sample_stats_warmup_attrs : attrs for sample_stats group
          - log_likelihood_attrs, log_likelihood_warmup_attrs : attrs for log_likelihood group
          - posterior_predictive_attrs, posterior_predictive_warmup_attrs : attrs for
            posterior_predictive group
          - predictions_attrs, predictions_warmup_attrs : attrs for predictions group
          - prior_attrs : attrs for prior group
          - sample_stats_prior_attrs : attrs for sample_stats_prior group
          - prior_predictive_attrs : attrs for prior_predictive group
  
      Returns
      -------
      InferenceData
      """
      return DictConverter(
          posterior=posterior,
          posterior_predictive=posterior_predictive,
          predictions=predictions,
          sample_stats=sample_stats,
          log_likelihood=log_likelihood,
          prior=prior,
          prior_predictive=prior_predictive,
          sample_stats_prior=sample_stats_prior,
          observed_data=observed_data,
          constant_data=constant_data,
          predictions_constant_data=predictions_constant_data,
          warmup_posterior=warmup_posterior,
          warmup_posterior_predictive=warmup_posterior_predictive,
          warmup_predictions=warmup_predictions,
          warmup_log_likelihood=warmup_log_likelihood,
          warmup_sample_stats=warmup_sample_stats,
          save_warmup=save_warmup,
          index_origin=index_origin,
          coords=coords,
          dims=dims,
          pred_dims=pred_dims,
          pred_coords=pred_coords,
          attrs=attrs,
          **kwargs,
      ).to_inference_data()
  
imports: import warnings
  from typing import Optional
  from ..rcparams import rcParams
  from .base import dict_to_dataset, requires
  from .inference_data import WARMUP_TAG, InferenceData
label_desc: Use image node_id 1 for calling a global function with example usage: from_dict(posterior) and returns: DictConverter