code: def remove_missing_entries(dataset):
      """Remove missing entries.
  
      Some of the datasets have missing entries that sneak in as zero'd out
      feature vectors. Get rid of them.
      """
      for i, (X, y, w, ids) in enumerate(dataset.itershards()):
          available_rows = X.any(axis=1)
          print(
              "Shard %d has %d missing entries."
              % (i, np.count_nonzero(~available_rows))
          )
          X = X[available_rows]
          y = y[available_rows]
          w = w[available_rows]
          ids = ids[available_rows]
          dataset.set_shard(i, X, y, w, ids)
  
file_path: deepchem/examples/factors/FACTORS_datasets.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import os
  import shutil
  import time
  import numpy
  import deepchem
  from factors_features import factors_descriptors
label_desc: Use image node_id 1 for calling a global function with example usage: remove_missing_entries(dataset) without return types