Replaced Depricated scalar_summary with new functions of tf

google · Jul 25, 2019 · bce7131 · bce7131
1 parent e7c8eb1
commit bce7131
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Showing 2 changed files with 2 additions and 2 deletions.
diff --git a/code/cifar_train_baseline.py b/code/cifar_train_baseline.py
@@ -247,7 +247,7 @@ def train_inception_baseline(max_step_run):
           labels=one_hot_labels, logits=logits)
       total_loss = tf.reduce_mean(total_loss)
 
-      tf.contrib.deprecated.scalar_summary('Total Loss', total_loss)
+      tf.compat.v1.summary.scalar('Total Loss', total_loss)
 
       decay_steps = int(
           num_samples_per_epoch / FLAGS.batch_size * FLAGS.num_epochs_per_decay)

diff --git a/code/resnet_model.py b/code/resnet_model.py
@@ -124,7 +124,7 @@ def build_model(self):
   def _build_train_op(self):
     """Build training specific ops for the graph."""
     self.lrn_rate = tf.constant(self.hps.lrn_rate, tf.float32)
-    tf.contrib.deprecated.scalar_summary('learning rate', self.lrn_rate)
+    tf.compat.v1.summary.scalar('learning rate', self.lrn_rate)
 
     trainable_variables = tf.trainable_variables()
     grads = tf.gradients(self.cost, trainable_variables)