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Experimental context manager for use when defining a custom summary op.
@tf_contextlib.contextmanager
tf.summary.experimental.summary_scope( name, default_name='summary', values=None )
This behaves similarly to tf.name_scope
, except that it returns a generated
summary tag in addition to the scope name. The tag is structurally similar to
the scope name - derived from the user-provided name, prefixed with enclosing
name scopes if any - but we relax the constraint that it be uniquified, as
well as the character set limitation (so the user-provided name can contain
characters not legal for scope names; in the scope name these are removed).
This makes the summary tag more predictable and consistent for the user.
For example, to define a new summary op called my_op
:
def my_op(name, my_value, step):
with tf.summary.summary_scope(name, "MyOp", [my_value]) as (tag, scope):
my_value = tf.convert_to_tensor(my_value)
return tf.summary.write(tag, my_value, step=step)
Args | |
---|---|
name
|
string name for the summary. |
default_name
|
Optional; if provided, used as default name of the summary. |
values
|
Optional; passed as values parameter to name_scope.
|
Yields | |
---|---|
A tuple (tag, scope) as described above.
|