class_docstr: Represents a feature column abstraction.
  
  WARNING: Do not subclass this layer unless you know what you are doing:
  the API is subject to future changes.
  
  To distinguish between the concept of a feature family and a specific binary
  feature within a family, we refer to a feature family like "country" as a
  feature column. For example, we can have a feature in a `tf.Example` format:
    {key: "country",  value: [ "US" ]}
  In this example the value of feature is "US" and "country" refers to the
  column of the feature.
  
  This class is an abstract class. Users should not create instances of this.
docstr: Allows feature columns to be sorted in Python 3 as they are in Python 2.
  
  Feature columns need to occasionally be sortable, for example when used as
  keys in a features dictionary passed to a layer.
  
  In CPython, `__lt__` must be defined for all objects in the
  sequence being sorted.
  
  If any objects in the sequence being sorted do not have an `__lt__` method
  compatible with feature column objects (such as strings), then CPython will
  fall back to using the `__gt__` method below.
  https://docs.python.org/3/library/stdtypes.html#list.sort
  
  Args:
    other: The other object to compare to.
  
  Returns:
    True if the string representation of this object is lexicographically less
    than the string representation of `other`. For FeatureColumn objects,
    this looks like "<__main__.FeatureColumn object at 0xa>".
docstr_tok: ["Allows","feature","columns","to","be","sorted","in","Python","3","as","they","are","in","Python","2",".","Feature","columns","need","to","occasionally","be","sortable",",","for","example","when","used","as","keys","in","a","features","dictionary","passed","to","a","layer",".","In","CPython",",","`","__lt__","`","must","be","defined","for","all","objects","in","the","sequence","being","sorted",".","If","any","objects","in","the","sequence","being","sorted","do","not","have","an","`","__lt__","`","method","compatible","with","feature","column","objects","(","such","as","strings",")",",","then","CPython","will","fall","back","to","using","the","`","__gt__","`","method","below",".","https",":","\/\/docs.python.org\/3\/library\/stdtypes.html","#","list.sort","Args",":","other",":","The","other","object","to","compare","to",".","Returns",":","True","if","the","string","representation","of","this","object","is","lexicographically","less","than","the","string","representation","of","`","other","`",".","For","FeatureColumn","objects",",","this","looks","like","``","<","__main__.FeatureColumn","object","at","0xa",">","''","."]
code: def __lt__(self, other):
      """Allows feature columns to be sorted in Python 3 as they are in Python 2.
  
      Feature columns need to occasionally be sortable, for example when used as
      keys in a features dictionary passed to a layer.
  
      In CPython, `__lt__` must be defined for all objects in the
      sequence being sorted.
  
      If any objects in the sequence being sorted do not have an `__lt__` method
      compatible with feature column objects (such as strings), then CPython will
      fall back to using the `__gt__` method below.
      https://docs.python.org/3/library/stdtypes.html#list.sort
  
      Args:
        other: The other object to compare to.
  
      Returns:
        True if the string representation of this object is lexicographically less
        than the string representation of `other`. For FeatureColumn objects,
        this looks like "<__main__.FeatureColumn object at 0xa>".
      """
      return str(self) < str(other)
  
file_path: tensorflow/tensorflow/python/feature_column/feature_column_v2_types.py
imports: import abc
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling the FeatureColumn obj's underlying member method code with example usage: obj.__lt__(other) and returns: unknown