class_docstr: Manages placeholders associated with batch of graphs and their topology
docstr: Converts the current batch of mol_graphs into tensorflow feed_dict.
  
  Assigns the graph information in array of ConvMol objects to the
  placeholders tensors
  
  params
  ------
  batch : np.ndarray
    Array of ConvMol objects
  
  returns
  -------
  feed_dict : dict
    Can be merged with other feed_dicts for input into tensorflow
docstr_tok: ["Converts","the","current","batch","of","mol_graphs","into","tensorflow","feed_dict",".","Assigns","the","graph","information","in","array","of","ConvMol","objects","to","the","placeholders","tensors","params","--","--","--","batch",":","np.ndarray","Array","of","ConvMol","objects","returns","--","--","--","-","feed_dict",":","dict","Can","be","merged","with","other","feed_dicts","for","input","into","tensorflow"]
code: def batch_to_feed_dict(self, batch):
      """Converts the current batch of mol_graphs into tensorflow feed_dict.
  
      Assigns the graph information in array of ConvMol objects to the
      placeholders tensors
  
      params
      ------
      batch : np.ndarray
        Array of ConvMol objects
  
      returns
      -------
      feed_dict : dict
        Can be merged with other feed_dicts for input into tensorflow
      """
      # Merge mol conv objects
      batch = ConvMol.agglomerate_mols(batch)
      atoms = batch.get_atom_features()
      deg_adj_lists = [
          batch.deg_adj_lists[deg] for deg in range(1, self.max_deg + 1)
      ]
  
      # Generate dicts
      deg_adj_dict = dict(
          list(zip(self.deg_adj_lists_placeholders, deg_adj_lists))
      )
      atoms_dict = {
          self.atom_features_placeholder: atoms,
          self.deg_slice_placeholder: batch.deg_slice,
          self.membership_placeholder: batch.membership,
      }
      return merge_dicts([atoms_dict, deg_adj_dict])
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import warnings
  import numpy
  import tensorflow
  from deepchem.nn.copy import Input
  from deepchem.feat.mol_graphs import ConvMol
label_desc: Use image node_id 8 for calling the GraphTopology obj's underlying member method code with example usage: obj.batch_to_feed_dict(batch) and returns: merge_dicts