class_docstr: Sequence of ndarrays having variable first dimension sizes.
  
  This is a container that can store multiple ndarrays where each ndarray
  might have a different first dimension size but a *common* size for the
  remaining dimensions.
  
  More generally, an instance of :class:`ArraySequence` of length $N$ is
  composed of $N$ ndarrays of shape $(d_1, d_2, ... d_D)$ where $d_1$
  can vary in length between arrays but $(d_2, ..., d_D)$ have to be the
  same for every ndarray.
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docstr: Finalize process of appending several elements to `self`
  
  :meth:`append` can be a lot faster if it knows that it is appending
  several elements instead of a single element.  To tell the append
  method this is the case, use ``cache_build=True``.  This method
  finalizes the series of append operations after a call to
  :meth:`append` with ``cache_build=True``.
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code: def finalize_append(self):
      """Finalize process of appending several elements to `self`
  
      :meth:`append` can be a lot faster if it knows that it is appending
      several elements instead of a single element.  To tell the append
      method this is the case, use ``cache_build=True``.  This method
      finalizes the series of append operations after a call to
      :meth:`append` with ``cache_build=True``.
      """
      if self._build_cache is None:
          return
      self._build_cache.update_seq(self)
      self._build_cache = None
      self.shrink_data()
  
imports: import numbers
  from functools import reduce
  from operator import mul
  import numpy
label_desc: Use image node_id 10 for calling the ArraySequence obj's underlying member method code with example usage: obj.finalize_append() without return types