class_docstr: Simple class that holds information needed to run Tensorflow graph.
class_docstr_tok: ["Simple","class","that","holds","information","needed","to","run","Tensorflow","graph","."]
code: def get_feed_dict(named_values):
      feed_dict = {}
      placeholder_root = "placeholders"
      for name, value in named_values.items():
          feed_dict["{}/{}:0".format(placeholder_root, name)] = value
      return feed_dict
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import collections
  import pickle
  import os
  import time
  import warnings
  import numpy
  import pandas
  import tensorflow
  import tempfile
  from deepchem.models import Model
  from deepchem.metrics import from_one_hot
  from deepchem.nn import model_ops
  from deepchem.models.tensorflow_models import utils
  from deepchem.trans import undo_transforms
  from deepchem.utils.save import log
  from deepchem.utils.evaluate import Evaluator
  from deepchem.data import pad_features
  from tensorflow.contrib.layers.python.layers import batch_norm
label_desc: Use image node_id 4 for calling the TensorflowGraph obj's underlying member method code with example usage: obj.get_feed_dict(named_values) and returns: feed_dict