Merge remote-tracking branch 'remotes/mine/weave' into weave (8488e279) · Commits · 钟慕尧 / deepchem

deepchem/models/tf_new_models/graph_models.py

+7 −5

Original line number	Diff line number	Diff line
		@@ -161,6 +161,7 @@ class SequentialDAGGraph(SequentialGraph):
		self.output = layer(self.output)
		self.layers.append(layer)


		class SequentialWeaveGraph(SequentialGraph):
		"""SequentialGraph for Weave models
		"""
		@@ -171,8 +172,7 @@ class SequentialWeaveGraph(SequentialGraph):
		self.n_atom_feat = n_atom_feat
		self.n_pair_feat = n_pair_feat
		with self.graph.as_default():
		self.graph_topology = WeaveGraphTopology(self.max_atoms,
		self.n_atom_feat,
		self.graph_topology = WeaveGraphTopology(self.max_atoms, self.n_atom_feat,
		self.n_pair_feat)
		self.output = self.graph_topology.get_atom_features_placeholder()
		self.output_P = self.graph_topology.get_pair_features_placeholder()
		@@ -182,8 +182,9 @@ class SequentialWeaveGraph(SequentialGraph):
		"""Adds a new layer to model."""
		with self.graph.as_default():
		if type(layer).__name__ in ['WeaveLayer']:
		self.output, self.output_P = layer([self.output, self.output_P] +
		self.graph_topology.get_topology_placeholders())
		self.output, self.output_P = layer([
		self.output, self.output_P
		] + self.graph_topology.get_topology_placeholders())
		elif type(layer).__name__ in ['WeaveConcat']:
		self.output = layer(
		[self.output, self.graph_topology.atom_mask_placeholder])
		@@ -194,6 +195,7 @@ class SequentialWeaveGraph(SequentialGraph):
		self.output = layer(self.output)
		self.layers.append(layer)


		class SequentialSupportGraph(object):
		"""An analog of Keras Sequential model for test/support models."""

deepchem/models/tf_new_models/graph_topology.py

+15 −15

Original line number	Diff line number	Diff line
		@@ -393,10 +393,12 @@ class DAGGraphTopology(GraphTopology):
		output[ide] = self.batch_size * self.max_atoms
		return output


		class WeaveGraphTopology(GraphTopology):
		"""Manages placeholders associated with batch of graphs and their topology"""

		def __init__(self, max_atoms, n_atom_feat, n_pair_feat, name='Weave_topology'):
		def __init__(self, max_atoms, n_atom_feat, n_pair_feat,
		name='Weave_topology'):
		"""
		Parameters
		----------
		@@ -431,9 +433,7 @@ class WeaveGraphTopology(GraphTopology):
		shape=(None, self.max_atoms, self.max_atoms),
		name=self.name + '_pair_mask')
		self.membership_placeholder = tf.placeholder(
		dtype='int32',
		shape=(None,),
		name=self.name + '_membership')
		dtype='int32', shape=(None,), name=self.name + '_membership')
		# Define the list of tensors to be used as topology
		self.topology = [self.atom_mask_placeholder, self.pair_mask_placeholder]
		self.inputs = [self.atom_features_placeholder]
		@@ -467,14 +467,14 @@ class WeaveGraphTopology(GraphTopology):
		max_atoms = self.max_atoms
		for im, mol in enumerate(batch):
		n_atoms = mol.get_num_atoms()
		atom_feat.append(np.pad(mol.get_atom_features(), ((0, max_atoms - n_atoms),
		(0,0)),
		'constant'))
		atom_mask.append(np.array([1]n_atoms + [0](max_atoms-n_atoms), dtype=float))
		pair_feat.append(np.pad(mol.get_pair_features(), ((0, max_atoms - n_atoms),
		(0, max_atoms - n_atoms),
		(0,0)),
		atom_feat.append(
		np.pad(mol.get_atom_features(), ((0, max_atoms - n_atoms), (0, 0)),
		'constant'))
		atom_mask.append(
		np.array([1] * n_atoms + [0] * (max_atoms - n_atoms), dtype=float))
		pair_feat.append(
		np.pad(mol.get_pair_features(), ((0, max_atoms - n_atoms), (
		0, max_atoms - n_atoms), (0, 0)), 'constant'))
		pair_mask.append(np.array([[1]n_atoms + [0](max_atoms-n_atoms)]*n_atoms + \
		[[0]max_atoms](max_atoms-n_atoms), dtype=float))
		membership.extend([im] * n_atoms)

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