code: def extract(condition, a):
      """
      Return the elements of a tensor that satisfy some condition.
  
      This is equivalent to ``mt.compress(ravel(condition), ravel(arr))``.  If
      `condition` is boolean ``mt.extract`` is equivalent to ``arr[condition]``.
  
      Note that `place` does the exact opposite of `extract`.
  
      Parameters
      ----------
      condition : array_like
          An array whose nonzero or True entries indicate the elements of `arr`
          to extract.
      a : array_like
          Input tensor of the same size as `condition`.
  
      Returns
      -------
      extract : Tensor
          Rank 1 tensor of values from `arr` where `condition` is True.
  
      See Also
      --------
      take, put, copyto, compress, place
  
      Examples
      --------
      >>> import mars.tensor as mt
  
      >>> arr = mt.arange(12).reshape((3, 4))
      >>> arr.execute()
      array([[ 0,  1,  2,  3],
             [ 4,  5,  6,  7],
             [ 8,  9, 10, 11]])
      >>> condition = mt.mod(arr, 3)==0
      >>> condition.execute()
      array([[ True, False, False,  True],
             [False, False,  True, False],
             [False,  True, False, False]])
      >>> mt.extract(condition, arr).execute()
      array([0, 3, 6, 9])
  
  
      If `condition` is boolean:
  
      >>> arr[condition].execute()
      array([0, 3, 6, 9])
  
      """
      condition = astensor(condition, dtype=bool)
      return a[condition]
  
label_desc: Use image node_id 1 for calling a global function with example usage: extract(condition, a) and returns: a