alphashare test

from deepchem.models.tensorgraph.layers import LSTMStep

from deepchem.models.tensorgraph.layers import AttnLSTMEmbedding

from deepchem.models.tensorgraph.layers import IterRefLSTMEmbedding

from deepchem.models.tensorgraph.layers import AlphaShare

#from deepchem.models.tensorgraph.layers import BetaShare

#from deepchem.models.tensorgraph.layers import SluiceLoss

import deepchem as dc

      for deg_adj in deg_adjs:

        deg_adjs_tf.append(tf.convert_to_tensor(deg_adj, dtype=tf.int32))

      args = [atom_features, degree_slice, membership] + deg_adjs_tf

      test_1 = tf.convert_to_tensor(test_1, dtype=tf.float32)

      out_tensor = GraphConv(out_channels)(*args)

      sess.run(tf.global_variables_initializer())

      out_tensor = out_tensor.eval()

      assert test_out.shape == (n_test, n_feat)

      assert support_out.shape == (n_support, n_feat)

  def test_alpha_share(self):

    """test that alpha share works correctly"""

    batch_size = 50

    length = 10

    test_1 = np.random.rand(batch_size, length)

    test_2 = np.random.rand(batch_size, length)

    with self.test_session() as sess:

      test_1 = tf.convert_to_tensor(test_1, dtype=tf.float32)

      test_2 = tf.convert_to_tensor(test_2, dtype=tf.float32)

      out_tensor = AlphaShare(in_layers=[test_1, test_2])

      sess.run(tf.global_variables_initializer())

      test_1_out_tensor = out_tensor[0].eval

      test_2_out_tensor = out_tensor[1].eval

      assert test_1.shape == test_1_out_tensor.shape

      assert test_2.shape == test_2_out_tensor.shape

  # TODO(rbharath): This test should pass. Fix it!

  #def test_graph_pool(self):

  #  """Test that GraphPool can be invoked."""

      assert result == 1.5

      result = sess.run(tf.gradients(v, v))

      assert result[0] == 1.0

TestLayers.test_alpha_share()