74672a0cb8d5f42eedb4298c2c5f4ac5390994fc,deepchem/models/tensorgraph/models/scscore.py,Scscore,Scscore_1,#,8

Before Change

  label = Label(shape=(300,))

  loss = Hingeloss(in_layers=[label, hidden_5])
  tg.set_loss(loss)
  output = Sigmoid(in_layers=[hidden_5])
  tg.add_output(output)

After Change

  dense_reactant_1 = Dense(
      out_channels=300, in_layers=[reactant_features], activation_fn=tf.nn.relu)
  dense_product_1 = dense_reactant_1.shared(in_layers=[product_features])
  dense_reactant_2 = Dense(
      out_channels=300, in_layers=[dense_reactant_1], activation_fn=tf.nn.relu)
  dense_product_2 = dense_reactant_2.shared(in_layers=[dense_product_1])
  dense_reactant_3 = Dense(
      out_channels=300, in_layers=[dense_reactant_2], activation_fn=tf.nn.relu)
  dense_product_3 = dense_reactant_3.shared(in_layers=[dense_product_2])
  dense_reactant_4 = Dense(
      out_channels=300, in_layers=[dense_reactant_3], activation_fn=tf.nn.relu)
  dense_product_4 = dense_reactant_4.shared(in_layers=[dense_product_3])
  dense_reactant_5 = Dense(
      out_channels=300, in_layers=[dense_reactant_4], activation_fn=tf.nn.relu)
  dense_product_5 = dense_reactant_5.shared(in_layers=[dense_product_4])

  output_dense = Add(in_layers=[dense_reactant_5, dense_product_5])

  output = Sigmoid(in_layers=[output_dense])
  tg.add_output(output)

Instances