class_docstr: Manages issues related to underperforming group examples.
  
  Note: The `min_cluster_samples` argument should not be confused with the
  `min_samples` argument of sklearn.cluster.DBSCAN.
  
  Examples
  --------
  >>> from cleanlab import Datalab
  >>> import numpy as np
  >>> X = np.random.normal(size=(50, 2))
  >>> y = np.random.randint(2, size=50)
  >>> pred_probs = X / X.sum(axis=1, keepdims=True)
  >>> data = {"X": X, "y": y}
  >>> lab = Datalab(data, label_name="y")
  >>> issue_types={"underperforming_group": {"clustering_kwargs": {"eps": 0.5}}}
  >>> lab.find_issues(pred_probs=pred_probs, features=X, issue_types=issue_types)
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docstr: Determine if a knn_graph is provided in the kwargs or if one is already stored in the associated Datalab instance.
docstr_tok: ["Determine","if","a","knn_graph","is","provided","in","the","kwargs","or","if","one","is","already","stored","in","the","associated","Datalab","instance","."]
code: def _process_knn_graph_from_inputs(
      self, kwargs: Dict[str, Any]
  ) -> Union[csr_matrix, None]:
      """Determine if a knn_graph is provided in the kwargs or if one is already stored in the associated Datalab instance."""
      knn_graph_kwargs: Optional[csr_matrix] = kwargs.get(
          "knn_graph", None
      )
      knn_graph_stats = self.datalab.get_info("statistics").get(
          "weighted_knn_graph", None
      )
  
      knn_graph: Optional[csr_matrix] = None
      if knn_graph_kwargs is not None:
          knn_graph = knn_graph_kwargs
      elif knn_graph_stats is not None:
          knn_graph = knn_graph_stats
  
      if isinstance(knn_graph, csr_matrix) and kwargs.get("k", 0) > (
          knn_graph.nnz // knn_graph.shape[0]
      ):
          # If the provided knn graph is insufficient, then we need to recompute the knn graph
          # with the provided features
          knn_graph = None
  
      return knn_graph
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union, Tuple
  import warnings
  import inspect
  import numpy
  import pandas
  from scipy.sparse import csr_matrix
  from sklearn.neighbors import NearestNeighbors
  from sklearn.exceptions import NotFittedError
  from sklearn.utils.validation import check_is_fitted
  from sklearn.cluster import DBSCAN
  from cleanlab.datalab.internal.issue_manager import IssueManager
  from cleanlab.rank import get_self_confidence_for_each_label
label_desc: Use image node_id 7 for calling the UnderperformingGroupIssueManager obj's underlying member method code with example usage: obj._process_knn_graph_from_inputs(kwargs) and returns: knn_graph