class_docstr: Abstract InputPipeline class. All input pipelines must inherit from this.
  An InputPipeline defines how data is read, parsed, and separated into
  features and labels.
  
  Params:
    shuffle: If true, shuffle the data.
    num_epochs: Number of times to iterate through the dataset. If None,
      iterate forever.
class_docstr_tok: ["Abstract","InputPipeline","class",".","All","input","pipelines","must","inherit","from","this",".","An","InputPipeline","defines","how","data","is","read",",","parsed",",","and","separated","into","features","and","labels",".","Params",":","shuffle",":","If","true",",","shuffle","the","data",".","num_epochs",":","Number","of","times","to","iterate","through","the","dataset",".","If","None",",","iterate","forever","."]
docstr: Utility function to read all available items from a DataProvider.
      
docstr_tok: ["Utility","function","to","read","all","available","items","from","a","DataProvider","."]
code: def read_from_data_provider(data_provider):
      """Utility function to read all available items from a DataProvider."""
      item_values = data_provider.get(list(data_provider.list_items()))
      items_dict = dict(zip(data_provider.list_items(), item_values))
      return items_dict
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import abc
  import sys
  import six
  import tensorflow
  from tensorflow.contrib.slim.python.slim.data import tfexample_decoder
  from seq2seq.configurable import Configurable
  from seq2seq.data import split_tokens_decoder, parallel_data_provider
  from seq2seq.data.sequence_example_decoder import TFSEquenceExampleDecoder
label_desc: Use image node_id 6 for calling the InputPipeline obj's underlying member method code with example usage: obj.read_from_data_provider(data_provider) and returns: items_dict