class_docstr: Helper for dimensionality reduction to the innermost dimension of a tensor.
  
  This class wraps sklearn.decomposition classes to help them apply to arbitrary
  rank tensors. It saves lots of annoying reshaping.
  
  See the original sklearn.decomposition documentation:
  http://scikit-learn.org/stable/modules/classes.html#module-sklearn.decomposition
class_docstr_tok: ["Helper","for","dimensionality","reduction","to","the","innermost","dimension","of","a","tensor",".","This","class","wraps","sklearn.decomposition","classes","to","help","them","apply","to","arbitrary","rank","tensors",".","It","saves","lots","of","annoying","reshaping",".","See","the","original","sklearn.decomposition","documentation",":","http",":","\/\/scikit-learn.org\/stable\/modules\/classes.html","#","module-sklearn.decomposition"]
code: def __dir__(self):
      dynamic_attrs = [
          name[:-1]
          for name in dir(self._reducer)
          if name[-1] == "_" and name[0] != "_"
      ]
  
      return (
          list(ChannelReducer.__dict__.keys())
          + list(self.__dict__.keys())
          + dynamic_attrs
      )
  
file_path: lucid/lucid/misc/channel_reducer.py
imports: import numpy
  import sklearn.decomposition
label_desc: Use image node_id 8 for calling the ChannelReducer obj's underlying member method code with example usage: obj.__dir__() and returns: unknown