class_docstr: Transform features using quantiles information.
  
  Stripped down version of sklearn.preprocessing.QuantileTransformer.
  https://github.com/scikit-learn/scikit-learn/blob/
  863e58fcd5ce960b4af60362b44d4f33f08c0f97/sklearn/preprocessing/_data.py
  
  Putting directly in ddsp library to avoid dependency on sklearn that breaks
  when pickling and unpickling from different versions of sklearn.
class_docstr_tok: ["Transform","features","using","quantiles","information",".","Stripped","down","version","of","sklearn.preprocessing.QuantileTransformer",".","https",":","\/\/github.com\/scikit-learn\/scikit-learn\/blob\/","863e58fcd5ce960b4af60362b44d4f33f08c0f97\/sklearn\/preprocessing\/_data.py","Putting","directly","in","ddsp","library","to","avoid","dependency","on","sklearn","that","breaks","when","pickling","and","unpickling","from","different","versions","of","sklearn","."]
docstr: Feature-wise transformation of the data.
docstr_tok: ["Feature-wise","transformation","of","the","data","."]
code: def transform(self, x):
      """Feature-wise transformation of the data."""
      return self._transform(x, inverse=False)
  
file_path: ddsp/ddsp/training/postprocessing.py
imports: from ddsp import spectral_ops
  from ddsp.core import hz_to_midi
  import numpy
  from scipy import stats
  import tensorflow.compat.v2
label_desc: Use image node_id 6 for calling the QuantileTransformer obj's underlying member method code with example usage: obj.transform(x) and returns: self