Update concat_v2 to be concat to match 1.0 final

Fixes #1014

resnet/cifar_input.py

@@ -100,7 +100,7 @@ def build_input(dataset, data_path, batch_size, mode):
   labels = tf.reshape(labels, [batch_size, 1])
   indices = tf.reshape(tf.range(0, batch_size, 1), [batch_size, 1])
   labels = tf.sparse_to_dense(
-      tf.concat_v2(values=[indices, labels], axis=1),
+      tf.concat(values=[indices, labels], axis=1),
       [batch_size, num_classes], 1.0, 0.0)
 
   assert len(images.get_shape()) == 4

tutorials/rnn/ptb/ptb_word_lm.py

@@ -146,7 +146,7 @@ class PTBModel(object):
         (cell_output, state) = cell(inputs[:, time_step, :], state)
         outputs.append(cell_output)
 
-    output = tf.reshape(tf.concat_v2(outputs, 1), [-1, size])
+    output = tf.reshape(tf.concat(outputs, 1), [-1, size])
     softmax_w = tf.get_variable(
         "softmax_w", [size, vocab_size], dtype=data_type())
     softmax_b = tf.get_variable("softmax_b", [vocab_size], dtype=data_type())