Merge pull request #804 from peastman/networkx (88e49ce8) · Commits · 钟慕尧 / deepchem

deepchem/models/tensorgraph/tensor_graph.py

+24 −21

Original line number	Diff line number	Diff line
		@@ -2,7 +2,6 @@ import pickle
		import threading
		import time

		import networkx as nx
		import collections
		import numpy as np
		import os
		@@ -56,7 +55,6 @@ class TensorGraph(Model):
		"""

		# Layer Management
		self.nxgraph = nx.DiGraph()
		self.layers = dict()
		self.features = list()
		self.labels = list()
		@@ -108,11 +106,9 @@ class TensorGraph(Model):
		self.labels.append(layer)
		if isinstance(layer, Weights):
		self.task_weights.append(layer)
		self.nxgraph.add_node(layer.name)
		self.layers[layer.name] = layer
		for in_layer in layer.in_layers:
		self._add_layer(in_layer)
		self.nxgraph.add_edge(in_layer.name, layer.name)

		def fit(self,
		dataset,
		@@ -410,7 +406,19 @@ class TensorGraph(Model):
		return self.predict_proba_on_generator(generator, transformers, outputs)

		def topsort(self):
		return nx.topological_sort(self.nxgraph)

		def add_layers_to_list(layer, sorted_layers):
		if layer in sorted_layers:
		return
		for in_layer in layer.in_layers:
		add_layers_to_list(in_layer, sorted_layers)
		sorted_layers.append(layer)

		sorted_layers = []
		for l in self.features + self.labels + self.task_weights + self.outputs:
		add_layers_to_list(l, sorted_layers)
		add_layers_to_list(self.loss, sorted_layers)
		return sorted_layers

		def build(self):
		if self.built:
		@@ -420,15 +428,13 @@ class TensorGraph(Model):
		if self.random_seed is not None:
		tf.set_random_seed(self.random_seed)
		self._install_queue()
		order = self.topsort()
		for node in order:
		with tf.name_scope(node):
		node_layer = self.layers[node]
		node_layer.create_tensor(training=self._training_placeholder)
		self.rnn_initial_states += node_layer.rnn_initial_states
		self.rnn_final_states += node_layer.rnn_final_states
		self.rnn_zero_states += node_layer.rnn_zero_states
		node_layer.add_summary_to_tg()
		for layer in self.topsort():
		with tf.name_scope(layer.name):
		layer.create_tensor(training=self._training_placeholder)
		self.rnn_initial_states += layer.rnn_initial_states
		self.rnn_final_states += layer.rnn_final_states
		self.rnn_zero_states += layer.rnn_zero_states
		layer.add_summary_to_tg()
		self.session = tf.Session()

		self.built = True
		@@ -475,7 +481,6 @@ class TensorGraph(Model):
		pre_q_inputs.append(pre_q_input)

		layer.in_layers.append(q)
		self.nxgraph.add_edge(q.name, layer.name)

		self._add_layer(q)
		self.input_queue = q
		@@ -533,9 +538,8 @@ class TensorGraph(Model):
		out_tensors = []
		if self.built:
		must_restore = True
		for node in self.topsort():
		node_layer = self.layers[node]
		out_tensors.append(node_layer.none_tensors())
		for layer in self.topsort():
		out_tensors.append(layer.none_tensors())
		optimizer = self.optimizer
		self.optimizer = None
		training_placeholder = self._training_placeholder
		@@ -554,9 +558,8 @@ class TensorGraph(Model):

		# add out_tensor back to everyone
		if must_restore:
		for index, node in enumerate(self.topsort()):
		node_layer = self.layers[node]
		node_layer.set_tensors(out_tensors[index])
		for index, layer in enumerate(self.topsort()):
		layer.set_tensors(out_tensors[index])
		self._training_placeholder = training_placeholder
		self.optimizer = optimizer
		self.built = True

deepchem/utils/rdkit_util.py

+2 −1

Original line number	Diff line number	Diff line
		import logging

		import networkx as nx
		import numpy as np
		import os

		@@ -223,6 +222,7 @@ class PdbqtLigandWriter(object):
		The single public function of this class.
		It converts a molecule and a pdb file into a pdbqt file stored in outfile
		"""
		import networkx as nx
		self._create_pdb_map()
		self._mol_to_graph()
		self._get_rotatable_bonds()
		@@ -347,6 +347,7 @@ class PdbqtLigandWriter(object):
		atoms are nodes, and bonds are vertices
		store as self.graph
		"""
		import networkx as nx
		G = nx.Graph()
		num_atoms = self.mol.GetNumAtoms()
		G.add_nodes_from(range(num_atoms))

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