class_docstr: Stores sufficient statistics for the current chunk of document(s) whenever Hdp model is updated with new corpus.
  These stats are used when updating lambda and top level sticks. The statistics include number of documents in the
  chunk, length of words in the documents and top level truncation level.
class_docstr_tok: ["Stores","sufficient","statistics","for","the","current","chunk","of","document","(","s",")","whenever","Hdp","model","is","updated","with","new","corpus",".","These","stats","are","used","when","updating","lambda","and","top","level","sticks",".","The","statistics","include","number","of","documents","in","the","chunk",",","length","of","words","in","the","documents","and","top","level","truncation","level","."]
docstr: Fill the sticks and beta array with 0 scalar value.
code: def set_zero(self):
      """Fill the sticks and beta array with 0 scalar value."""
      self.m_var_sticks_ss.fill(0.0)
      self.m_var_beta_ss.fill(0.0)
  
imports: import logging
  import time
  import warnings
  import numpy
  from scipy.special import gammaln, psi
  from gensim import interfaces, utils, matutils
  from gensim.matutils import dirichlet_expectation, mean_absolute_difference
  from gensim.models import basemodel, ldamodel
  from gensim.utils import deprecated
label_desc: Use image node_id 2 for calling the SuffStats obj's underlying member method code with example usage: obj.set_zero() without return types