def __init__(<EOL>self,<EOL>allele_to_allele_specific_models=None,<EOL>class1_pan_allele_models=None,<EOL>allele_to_fixed_length_sequence=None,<EOL>manifest_df=None,<EOL>allele_to_percent_rank_transform=None,<EOL>metadata_dataframes=None):
if allele_to_allele_specific_models is None:<EOL><INDENT>allele_to_allele_specific_models = {}<EOL><DEDENT>if class1_pan_allele_models is None:<EOL><INDENT>class1_pan_allele_models = []<EOL><DEDENT>if class1_pan_allele_models:<EOL><INDENT>assert allele_to_fixed_length_sequence, "<STR_LIT>"<EOL><DEDENT>self.allele_to_allele_specific_models = allele_to_allele_specific_models<EOL>self.class1_pan_allele_models = class1_pan_allele_models<EOL>self.allele_to_fixed_length_sequence = allele_to_fixed_length_sequence<EOL>self._manifest_df = manifest_df<EOL>if not allele_to_percent_rank_transform:<EOL><INDENT>allele_to_percent_rank_transform = {}<EOL><DEDENT>self.allele_to_percent_rank_transform = allele_to_percent_rank_transform<EOL>self.metadata_dataframes = metadata_dataframes<EOL>self._cache = {}<EOL>
Parameters
----------
allele_to_allele_specific_models : dict of string -> list of `Class1NeuralNetwork`
    Ensemble of single-allele models to use for each allele. 

class1_pan_allele_models : list of `Class1NeuralNetwork`
    Ensemble of pan-allele models.

allele_to_fixed_length_sequence : dict of string -> string
    Required only if class1_pan_allele_models is specified.

manifest_df : `pandas.DataFrame`, optional
    Must have columns: model_name, allele, config_json, model.
    Only required if you want to update an existing serialization of a
    Class1AffinityPredictor. Otherwise this dataframe will be generated
    automatically based on the supplied models.

allele_to_percent_rank_transform : dict of string -> `PercentRankTransform`, optional
    `PercentRankTransform` instances to use for each allele

metadata_dataframes : dict of string -> pandas.DataFrame, optional
    Optional additional dataframes to write to the models dir when
    save() is called. Useful for tracking provenance.