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: :return: tensorflow dtypes of the window.
docstr_tok: [":","return",":","tensorflow","dtypes","of","the","window","."]
code: def tf_dtypes(self):
      """
      :return: tensorflow dtypes of the window.
      """
      dtypes = {}
      for name in list(self._dtypes):
          dtypes[name] = self._dtypes[name]
          dtypes[LOCATION_FORMAT.format(name)] = BUFFER_POSITION_DTYPE
      return dtypes
  
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 5 for calling the ImageWindow obj's underlying member method code with example usage: obj.tf_dtypes() and returns: dtypes