all but sluice_loss (8974ff86) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/layers.py

+12 −3

Original line number	Diff line number	Diff line
		@@ -2613,10 +2613,10 @@ def AlphaShare(in_layers=None, **kwargs):
		"""
		output_layers = []
		alpha_share = AlphaShareLayer(in_layers=in_layers, **kwargs)
		num_outputs = len(kwargs['in_layers'])
		num_outputs = len(in_layers)
		for num_layer in range(0, num_outputs):
		output_layers.append(
		LayerSplitter(in_layers=alpha_share, output_num=num_layer))
		ls = LayerSplitter(output_num = num_layer, in_layers=alpha_share)
		output_layers.append(ls)
		return output_layers


		@@ -2713,8 +2713,17 @@ class LayerSplitter(Layer):
		def create_tensor(self, in_layers=None, set_tensors=True, **kwargs):
		inputs = self._get_input_tensors(in_layers)[0]
		self.out_tensor = inputs[self.output_num, :]
		out_tensor = self.out_tensor
		return self.out_tensor

		def none_tensors(self):
		out_tensor = self.out_tensor
		self.out_tensor = None
		return out_tensor

		def set_tensors(self, tensor):
		self.out_tensor = tensor


		class SluiceLoss(Layer):
		"""

deepchem/models/tensorgraph/tests/test_layers.py

+53 −19

Original line number	Diff line number	Diff line
		@@ -46,9 +46,11 @@ from deepchem.models.tensorgraph.layers import TensorWrapper
		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 Stack
		from deepchem.models.tensorgraph.layers import AlphaShareLayer
		from deepchem.models.tensorgraph.layers import BetaShare
		#from deepchem.models.tensorgraph.layers import SluiceLoss
		from deepchem.models.tensorgraph.layers import LayerSplitter

		import deepchem as dc

		@@ -468,23 +470,7 @@ class TestLayers(test_util.TensorFlowTestCase):
		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):
		@@ -632,4 +618,52 @@ class TestLayers(test_util.TensorFlowTestCase):
		result = sess.run(tf.gradients(v, v))
		assert result[0] == 1.0

		TestLayers.test_alpha_share()

		def test_alpha_share_layer(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 = AlphaShareLayer()(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

		def test_beta_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 = BetaShare()(test_1, test_2)
		sess.run(tf.global_variables_initializer())
		out_tensor.eval()
		assert test_1.shape == out_tensor.shape
		assert test_2.shape == out_tensor.shape

		def test_layer_splitter(self):
		input1 = np.arange(10).reshape(2,5)
		input2 = np.arange(10,20).reshape(2,5)

		with self.test_session() as sess:
		input1 = tf.convert_to_tensor(input1, dtype=tf.float32)
		input2 = tf.convert_to_tensor(input2, dtype=tf.float32)
		input_tensor = Stack()(input1, input2)
		output1 = LayerSplitter(0)(input_tensor)
		output2 = LayerSplitter(1)(input_tensor)
		sess.run(tf.global_variables_initializer())
		tf.assert_equal(input1, output1.eval())
		tf.assert_equal(input2, output2.eval())

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