View source on GitHub |
Merges summaries.
tf.compat.v1.summary.merge(
inputs, collections=None, name=None
)
Migrate to TF2
This API is not compatible with eager execution or tf.function
. To migrate
to TF2, this API can be omitted entirely, because in TF2 individual summary
ops, like tf.summary.scalar()
, write directly to the default summary writer
if one is active. Thus, it's not necessary to merge summaries or to manually
add the resulting merged summary output to the writer. See the usage example
shown below.
For a comprehensive tf.summary
migration guide, please follow
Migrating tf.summary usage to
TF 2.0.
TF1 & TF2 Usage Example
TF1:
dist = tf.compat.v1.placeholder(tf.float32, [100])
tf.compat.v1.summary.histogram(name="distribution", values=dist)
writer = tf.compat.v1.summary.FileWriter("/tmp/tf1_summary_example")
summaries = tf.compat.v1.summary.merge_all()
sess = tf.compat.v1.Session()
for step in range(100):
mean_moving_normal = np.random.normal(loc=step, scale=1, size=[100])
summ = sess.run(summaries, feed_dict={dist: mean_moving_normal})
writer.add_summary(summ, global_step=step)
TF2:
writer = tf.summary.create_file_writer("/tmp/tf2_summary_example")
for step in range(100):
mean_moving_normal = np.random.normal(loc=step, scale=1, size=[100])
with writer.as_default(step=step):
tf.summary.histogram(name='distribution', data=mean_moving_normal)
Description
This op creates a
Summary
protocol buffer that contains the union of all the values in the input
summaries.
When the Op is run, it reports an InvalidArgument
error if multiple values
in the summaries to merge use the same tag.
Returns | |
---|---|
A scalar Tensor of type string . The serialized Summary protocol
buffer resulting from the merging.
|
Raises | |
---|---|
RuntimeError
|
If called with eager mode enabled. |