class_docstr: Sets the given feature to 0 with a given probability
  
  Parameters
  ----------
  drop_proba:
      Probability that the feature gets dropped
  feature_name:
      Name of the feature to drop
class_docstr_tok: ["Sets","the","given","feature","to","0","with","a","given","probability","Parameters","--","--","--","--","--","drop_proba",":","Probability","that","the","feature","gets","dropped","feature_name",":","Name","of","the","feature","to","drop"]
code: def __call__(self, data):
      assert hasattr(data, self._feature_name)
      if random.random() < self._drop_proba:
          data[self._feature_name] = data[self._feature_name] * 0
      return data
  
imports: import random
  import torch
label_desc: Use image node_id 2 for calling the DropFeature obj's underlying member method code with example usage: obj.__call__(data) and returns: data