docstr: Constructs tensorflow feed from test/support sets.
docstr_tok: ["Constructs","tensorflow","feed","from","test\/support","sets","."]
code: def construct_feed_dict(
      self, test, support, training=True, add_phase=False
  ):
      """Constructs tensorflow feed from test/support sets."""
      # Generate dictionary elements for support
      feed_dict = self.model.support_graph_topology.batch_to_feed_dict(
          support.X
      )
      feed_dict[self.support_label_placeholder] = np.squeeze(support.y)
      # Get graph information for test
      batch_topo_dict = (
          self.model.test_graph_topology.batch_to_feed_dict(test.X)
      )
      feed_dict = merge_dicts([batch_topo_dict, feed_dict])
      # Generate dictionary elements for test
      feed_dict[self.test_label_placeholder] = np.squeeze(test.y)
      feed_dict[self.test_weight_placeholder] = np.squeeze(test.w)
  
      if add_phase:
          feed_dict[self.phase] = training
      return feed_dict
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import warnings
  import numpy
  import tensorflow
  import sys
  import time
  from deepchem.models import Model
  from deepchem.data import pad_batch
  from deepchem.data import NumpyDataset
  from deepchem.metrics import to_one_hot
  from deepchem.metrics import from_one_hot
  from deepchem.models.tf_new_models.graph_topology import merge_dicts
  from deepchem.nn import model_ops
  from deepchem.data import SupportGenerator
  from deepchem.data import EpisodeGenerator
  from deepchem.data import get_task_dataset
  from deepchem.data import get_single_task_test
  from deepchem.data import get_task_dataset_minus_support
  from deepchem.nn.copy import Input
label_desc: Use image node_id 4 for calling the SupportGraphClassifier obj's underlying member method code with example usage: obj.construct_feed_dict(test, support, training, add_phase) and returns: feed_dict