def test_metadata(self):
pb = self.compute_and_check_summary_pb('mona_lisa', self.images)
summary_metadata = pb.value[0].metadata
plugin_data = summary_metadata.plugin_data
self.assertEqual(plugin_data.plugin_name, metadata.PLUGIN_NAME)
content = summary_metadata.plugin_data.content
# There's no content, so successfully parsing is fine.
metadata.parse_plugin_metadata(content)
def test_metadata(self):
data = np.array(1, np.uint8, ndmin=4)
description = 'By Leonardo da Vinci'
pb = self.image('mona_lisa', data, description=description)
summary_metadata = pb.value[0].metadata
self.assertEqual(summary_metadata.summary_description, description)
plugin_data = summary_metadata.plugin_data
self.assertEqual(plugin_data.plugin_name, metadata.PLUGIN_NAME)
content = summary_metadata.plugin_data.content
# There's no content, so successfully parsing is fine.
metadata.parse_plugin_metadata(content)
def test_image(self):
with tf.compat.v1.Graph().as_default():
old_op = tf.compat.v1.summary.image(
"mona_lisa",
tf.image.convert_image_dtype(
tf.random.normal(shape=[1, 400, 200, 3]),
tf.uint8,
saturate=True,
),
)
old_value = self._value_from_op(old_op)
assert old_value.HasField("image"), old_value
new_value = data_compat.migrate_value(old_value)
self.assertEqual("mona_lisa/image/0", new_value.tag)
expected_metadata = image_metadata.create_summary_metadata(
display_name="mona_lisa/image/0",
description="",
converted_to_tensor=True,
)
# Check serialized submessages...
plugin_content = image_metadata.parse_plugin_metadata(
new_value.metadata.plugin_data.content
)
expected_content = image_metadata.parse_plugin_metadata(
expected_metadata.plugin_data.content
)
self.assertEqual(plugin_content, expected_content)
# ...then check full metadata except plugin content, since
# serialized forms need not be identical.
new_value.metadata.plugin_data.content = (
expected_metadata.plugin_data.content
)
self.assertEqual(expected_metadata, new_value.metadata)
self.assertTrue(new_value.HasField("tensor"))
(width, height, data) = tensor_util.make_ndarray(new_value.tensor)
self.assertEqual(b"200", width)
self.assertEqual(b"400", height)
self.assertEqual(
tf.compat.as_bytes(old_value.image.encoded_image_string), data
)