diff options
| author |  Dan Mané <danmane@google.com> | 2016-10-20 11:26:43 -0800 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2016-10-20 12:35:29 -0700 |
| commit | 8532897352ada1d8ecd3ca1dd17aaa869a42d4b8 (patch) | |
| tree | db2d24ac8d56d6ad4c135927e196fe5521cf3ec0 /tensorflow/examples/how_tos | |
| parent | 447dae3acf2cce61664d703555c7317da40fa2d4 (diff) | |
Shift tensorflow/examples over to the new summary ops.
This is a fairly minimal change, some functions have been cleaned up slightly
because the new summary ops dont need manual namespacing.
Behavior is approximately identical.
Change: 136745220
Diffstat (limited to 'tensorflow/examples/how_tos')
| -rw-r--r-- | tensorflow/examples/how_tos/reading_data/fully_connected_preloaded.py | 2 | ||||
| -rw-r--r-- | tensorflow/examples/how_tos/reading_data/fully_connected_preloaded_var.py | 2 |
2 files changed, 2 insertions, 2 deletions
diff --git a/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded.py b/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded.py index d0482568a2..7795248f82 100644 --- a/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded.py +++ b/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded.py @@ -75,7 +75,7 @@ def run_training(): eval_correct = mnist.evaluation(logits, labels) # Build the summary operation based on the TF collection of Summaries. - summary_op = tf.merge_all_summaries() + summary_op = tf.summary.merge_all() # Create a saver for writing training checkpoints. saver = tf.train.Saver() diff --git a/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded_var.py b/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded_var.py index d037b8731c..5325afbe60 100644 --- a/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded_var.py +++ b/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded_var.py @@ -81,7 +81,7 @@ def run_training(): eval_correct = mnist.evaluation(logits, labels) # Build the summary operation based on the TF collection of Summaries. - summary_op = tf.merge_all_summaries() + summary_op = tf.summary.merge_all() # Create a saver for writing training checkpoints. saver = tf.train.Saver() |