class_docstr: Class for building, loading and working with Hierarchical Navigable Small World index with SciKit-Learn
  Estimator compatible interface.
  Mostly drop-in replacement for sklearn.neighbors.NearestNeighbors (except for some parameters)
class_docstr_tok: ["Class","for","building",",","loading","and","working","with","Hierarchical","Navigable","Small","World","index","with","SciKit-Learn","Estimator","compatible","interface",".","Mostly","drop-in","replacement","for","sklearn.neighbors.NearestNeighbors","(","except","for","some","parameters",")"]
docstr: Returns
  -------
  Number of samples in the fitted data.
docstr_tok: ["Returns","--","--","--","-","Number","of","samples","in","the","fitted","data","."]
code: def n_samples_fit_(self):
      """
      Returns
      -------
      Number of samples in the fitted data.
      """
      self._check_index()
      return self._index_data.shape[0]
  
imports: import sys
  import os
  from six import iteritems
  from enum import IntEnum
  from contextlib import contextmanager
  import json
label_desc: Use image node_id 8 for calling the HnswEstimator obj's underlying member method code with example usage: obj.n_samples_fit_() and returns: self