class_docstr: Low dimensional projection of a term-document matrix.
  
  This is the class taking care of the 'core math': interfacing with corpora, splitting large corpora into chunks
  and merging them etc. This done through the higher-level :class:`~gensim.models.lsimodel.LsiModel` class.
  
  Notes
  -----
  The projection can be later updated by merging it with another :class:`~gensim.models.lsimodel.Projection`
  via  :meth:`~gensim.models.lsimodel.Projection.merge`. This is how incremental training actually happens.
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docstr: Get an empty Projection with the same parameters as the current object.
  
  Returns
  -------
  :class:`~gensim.models.lsimodel.Projection`
      An empty copy (without corpus) of the current projection.
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code: def empty_like(self):
      """Get an empty Projection with the same parameters as the current object.
  
      Returns
      -------
      :class:`~gensim.models.lsimodel.Projection`
          An empty copy (without corpus) of the current projection.
  
      """
      return Projection(
          self.m,
          self.k,
          power_iters=self.power_iters,
          extra_dims=self.extra_dims,
          random_seed=self.random_seed,
      )
  
imports: import logging
  import sys
  import time
  import numpy
  import scipy.linalg
  import scipy.sparse
  from scipy.sparse import sparsetools
  from gensim import interfaces, matutils, utils
  from gensim.models import basemodel
  from gensim.utils import is_empty
label_desc: Use image node_id 2 for calling the Projection obj's underlying member method code with example usage: obj.empty_like() and returns: Projection