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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def from_dict( posterior=None, *, posterior_predictive=None, sample_stats=None, prior=None, prior_predictive=None, sample_stats_prior=None, observed_data=None, coords=None, dims=None ):
 """Convert Dictionary data into an InferenceData object. Parameters posterior : dict posterior_predictive : dict sample_stats : dict "log_likelihood" variable for stats needs to be here. prior : dict prior_predictive : dict observed_data : dict coords : dict[str, iterable] 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[str, List(str)] A mapping from variables to a list of coordinate names for the variable. Returns ------- InferenceData object """

    return DictConverter(
        posterior=posterior,
        posterior_predictive=posterior_predictive,
        sample_stats=sample_stats,
        prior=prior,
        prior_predictive=prior_predictive,
        sample_stats_prior=sample_stats_prior,
        observed_data=observed_data,
        coords=coords,
        dims=dims,
    ).to_inference_data()