code: def _features(indices, feature_names, coef, x):
      names = mask(feature_names, indices)
      weights = mask(coef, indices)
      if x is not None:
          values = mask(x, indices)
          return [
              FeatureWeight(name, weight, value=value)
              for name, weight, value in zip(names, weights, values)
          ]
      else:
          return [
              FeatureWeight(name, weight)
              for name, weight in zip(names, weights)
          ]
  
file_path: eli5/eli5/_feature_weights.py
imports: from __future__ import absolute_import
  import numpy
  from eli5.base import FeatureWeights, FeatureWeight
  from .utils import argsort_k_largest_positive, argsort_k_smallest, mask
label_desc: Use image node_id 7 for calling a global function with example usage: _features(indices, feature_names, coef, x) and returns: unknown, unknown