def input_op(name,
data,
display_name=None,
description=None,
collections=None):
if (display_name == None):
display_name = name
summary_metadata = attention_metadata.create_summary_metadata(
display_name=display_name, description=description)
with tf.name_scope(name):
with tf.control_dependencies([tf.assert_type(data, tf.string)]):
return tf.summary.tensor_summary(name='attention_input_summary',
tensor=data,
collections=collections,
summary_metadata=summary_metadata)
def output_pb(name, data, display_name=None, description=None):
try:
tensor = tf.make_tensor_proto(data, dtype=tf.string)
except TypeError as e:
raise ValueError(e)
if display_name is None:
display_name = name
summary_metadata = attention_metadata.create_summary_metadata(
display_name=display_name, description=description)
summary = tf.Summary()
summary.value.add(tag='%s/attention_output_summary' % name,
metadata=summary_metadata,
tensor=tensor)
return summary