diff --git a/graphsage/supervised_train.py b/graphsage/supervised_train.py
index 9990cf9..c5bff00 100644
--- a/graphsage/supervised_train.py
+++ b/graphsage/supervised_train.py
@@ -144,7 +144,8 @@ def train(train_data, test_data=None):
             batch_size=FLAGS.batch_size,
             max_degree=FLAGS.max_degree, 
             context_pairs = context_pairs)
-    adj_info = tf.Variable(tf.constant(minibatch.adj, dtype=tf.int32), trainable=False, name="adj_info")
+    adj_info_ph = tf.placeholder(tf.int32, shape=minibatch.adj.shape)
+    adj_info = tf.Variable(adj_info_ph, trainable=False, name="adj_info")
 
     if FLAGS.model == 'graphsage_mean':
         # Create model
@@ -248,7 +249,7 @@ def train(train_data, test_data=None):
     summary_writer = tf.summary.FileWriter(log_dir(), sess.graph)
      
     # Init variables
-    sess.run(tf.global_variables_initializer())
+    sess.run(tf.global_variables_initializer(), feed_dict={adj_info_ph: minibatch.adj})
     
     # Train model
     
diff --git a/graphsage/unsupervised_train.py b/graphsage/unsupervised_train.py
index b3162fd..44ef609 100644
--- a/graphsage/unsupervised_train.py
+++ b/graphsage/unsupervised_train.py
@@ -146,7 +146,8 @@ def train(train_data, test_data=None):
             max_degree=FLAGS.max_degree, 
             num_neg_samples=FLAGS.neg_sample_size,
             context_pairs = context_pairs)
-    adj_info = tf.Variable(tf.constant(minibatch.adj, dtype=tf.int32), trainable=False, name="adj_info")
+    adj_info_ph = tf.placeholder(tf.int32, shape=minibatch.adj.shape)
+    adj_info = tf.Variable(adj_info_ph, trainable=False, name="adj_info")
 
     if FLAGS.model == 'graphsage_mean':
         # Create model
@@ -243,7 +244,7 @@ def train(train_data, test_data=None):
     summary_writer = tf.summary.FileWriter(log_dir(), sess.graph)
      
     # Init variables
-    sess.run(tf.global_variables_initializer())
+    sess.run(tf.global_variables_initializer(), feed_dict={adj_info_ph: minibatch.adj})
     
     # Train model