class_docstr: Private class used to pass the mappings as calculated by the AccessAnomaliesEstimator.
  An object representing the user and resource models
  (mapping from name to latent vector)
  and the relevant column names
code: def __init__(
      self,
      tenant_col: str,
      user_col: str,
      user_vec_col: str,
      res_col: str,
      res_vec_col: str,
      history_access_df: Optional[DataFrame],
      user2component_mappings_df: Optional[DataFrame],
      res2component_mappings_df: Optional[DataFrame],
      user_feature_vector_mapping_df: DataFrame,
      res_feature_vector_mapping_df: DataFrame,
  ):
      self.tenant_col = tenant_col
      self.user_col = user_col
      self.user_vec_col = user_vec_col
      self.res_col = res_col
      self.res_vec_col = res_vec_col
      self.history_access_df = history_access_df
      self.user2component_mappings_df = user2component_mappings_df
      self.res2component_mappings_df = res2component_mappings_df
      self.user_feature_vector_mapping_df = (
          user_feature_vector_mapping_df
      )
      self.res_feature_vector_mapping_df = res_feature_vector_mapping_df
  
      assert self.history_access_df is None or set(
          self.history_access_df.schema.fieldNames(),
      ) == {
          tenant_col,
          user_col,
          res_col,
      }, self.history_access_df.schema.fieldNames()
  
imports: import os
  from typing import List, Optional, Tuple
  from synapse.ml.cyber.anomaly.complement_access import ComplementAccessTransformer
  from synapse.ml.cyber.feature import indexers, scalers
  from synapse.ml.cyber.utils import spark_utils
  import numpy
  from pyspark import SQLContext
  from pyspark.ml import Estimator, Transformer
  from pyspark.ml.param.shared import Param, Params
  from pyspark.ml.recommendation import ALS
  from pyspark.sql import DataFrame, functions, types
label_desc: Use image node_id 1 to create a new _UserResourceFeatureVectorMapping object  with example: obj = _UserResourceFeatureVectorMapping(tenant_col, user_col, user_vec_col, res_col, res_vec_col, history_access_df, user2component_mappings_df, res2component_mappings_df, user_feature_vector_mapping_df, res_feature_vector_mapping_df)