code: def params():
      d2 = {
          "name": "hyper5",
          "radial": [
              [
                  1.5,
                  2.5,
                  3.5,
                  4.5,
                  5.5,
                  6.0,
                  6.5,
                  7.0,
                  7.5,
                  8.0,
                  8.5,
                  9.0,
                  9.5,
                  10.0,
                  10.5,
              ],
              [0.0, 2.0, 4.0],
              [0.05],
          ],
          "layer_sizes": [32, 16, 8],
          "learning_rate": 0.001,
          "epochs": 10,
          "frag1_num_atoms": 71,
          "frag2_num_atoms": 912,
          "complex_num_atoms": 982,
      }
      yield d2
      d2 = {
          "name": "original",
          "radial": [
              [
                  1.5,
                  2.0,
                  2.5,
                  3.0,
                  3.5,
                  4.0,
                  4.5,
                  5.0,
                  5.5,
                  6.0,
                  6.5,
                  7.0,
                  7.5,
                  8.0,
                  8.5,
                  9.0,
                  9.5,
                  10.0,
                  10.5,
                  11.0,
                  11.5,
                  12.0,
              ],
              [0.0, 4.0, 8.0],
              [0.4],
          ],
          "layer_sizes": [32, 32, 16],
          "learning_rate": 0.001,
          "epochs": 10,
          "frag1_num_atoms": 71,
          "frag2_num_atoms": 912,
          "complex_num_atoms": 982,
      }
      yield d2
  
file_path: deepchem/contrib/atomicconv/acnn/refined/tensor_graph_hyper_param_eval.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import unicode_literals
  import os
  import sys
  import deepchem
  import json
  import numpy
  import tensorflow
  from deepchem.models.atomic_conv import atomic_conv_model
  from deepchem.models.tensorgraph.layers import Layer, Feature, Label, L2Loss, AtomicConvolution, Transpose, Dense
  from deepchem.models import TensorGraph
  import numpy
  import tensorflow
  import itertools
  import time
label_desc: Use image node_id 1 for calling a global function with example usage: params() without return types