class_docstr: Each window is associated with a tuple of coordinates.
  These data properties are used to create TF
  placeholders or ``tf.data.Dataset`` when constructing a TF graph.
  Sampler read the data specifications and fill the placeholder/dataset.
class_docstr_tok: ["Each","window","is","associated","with","a","tuple","of","coordinates",".","These","data","properties","are","used","to","create","TF","placeholders","or","``","tf.data.Dataset","``","when","constructing","a","TF","graph",".","Sampler","read","the","data","specifications","and","fill","the","placeholder\/dataset","."]
docstr: Check whether the shape of the window is fully specified.
  
  :return: True indicates it's dynamic, False indicates
      the window size is fully specified.
docstr_tok: ["Check","whether","the","shape","of","the","window","is","fully","specified",".",":","return",":","True","indicates","it","'s","dynamic",",","False","indicates","the","window","size","is","fully","specified","."]
code: def _check_dynamic_shapes(self):
      """
      Check whether the shape of the window is fully specified.
  
      :return: True indicates it's dynamic, False indicates
          the window size is fully specified.
      """
      for shape in list(self._shapes.values()):
          try:
              for dim_length in shape:
                  if not dim_length or dim_length < 0:
                      return True
          except TypeError:
              return False
      return False
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import argparse
  import copy
  import numpy
  import tensorflow
  from tensorflow.python.data.util import nest
  from niftynet.utilities.util_common import ParserNamespace
label_desc: Use image node_id 13 for calling the ImageWindow obj's underlying member method code with example usage: obj._check_dynamic_shapes() and returns: False, False, True