class_docstr: FeedDictFlow.
  
  Generate a stream of batches from a dataset. It uses two queues, one for
  generating batch of data ids, and the other one to load data and apply pre
  processing. If continuous is `True`, data flow will never ends until `stop`
  is invoked, or `coord` interrupt threads.
  
  Arguments:
      feed_dict: `dict`. A TensorFlow formatted feed dict (with placeholders
          as keys and data as values).
      coord: `Coordinator`. A Tensorflow coordinator.
      num_threads: `int`. Total number of simultaneous threads to process data.
      max_queue: `int`. Maximum number of data stored in a queue.
      shuffle: `bool`. If True, data will be shuffle.
      continuous: `bool`. If True, when an epoch is over, same data will be
          feeded again.
      ensure_data_order: `bool`. Ensure that data order is keeped when using
          'next' to retrieve data (Processing will be slower).
      dprep_dict: dict. Optional data pre-processing parameter for performing
          real time data pre-processing. Keys must be placeholders and values
          `DataPreprocessing` subclass object.
      daug_dict: dict. Optional data augmentation parameter for performing
          real time data augmentation. Keys must be placeholders and values
          `DataAugmentation` subclass object.
      index_array: `list`. An optional list of index to be used instead of
          using the whole dataset indexes (Useful for validation split).
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docstr: next.
  
  Get the next feed dict.
  
  Returns:
      A TensorFlow feed dict, or 'False' if it has no more data.
docstr_tok: ["next",".","Get","the","next","feed","dict",".","Returns",":","A","TensorFlow","feed","dict",",","or","'False","'","if","it","has","no","more","data","."]
code: def next(self, timeout=None):
      """next.
  
      Get the next feed dict.
  
      Returns:
          A TensorFlow feed dict, or 'False' if it has no more data.
  
      """
      self.data_status.update()
      return self.feed_dict_queue.get(timeout=timeout)
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  import threading
  import tensorflow.compat.v1
  from .None import utils
label_desc: Use image node_id 2 for calling the FeedDictFlow obj's underlying member method code with example usage: obj.next(timeout) and returns: self