def test_tags(self):
"""Tests proper tags for each event/tensor."""
tensor_data = test_utils.get_random_mesh(100,
add_faces=True,
add_colors=True)
config_dict = {"foo": 1}
name = "foo"
events = self.mesh_events(
name,
tensor_data.vertices,
faces=tensor_data.faces,
colors=tensor_data.colors,
config_dict=config_dict,
step=333,
)
expected_names_set = frozenset(
name_tpl % name
for name_tpl in ["%s_VERTEX", "%s_FACE", "%s_COLOR"])
actual_names_set = frozenset(
[event.summary.value[0].tag for event in events])
self.assertEqual(expected_names_set, actual_names_set)
expected_bitmask = metadata.get_components_bitmask([
plugin_data_pb2.MeshPluginData.VERTEX,
plugin_data_pb2.MeshPluginData.FACE,
plugin_data_pb2.MeshPluginData.COLOR,
])
for event in events:
self.assertEqual(expected_bitmask,
self.get_metadata(event).components)
def test_get_tensor_summary(self):
"""Tests proper creation of tensor summary with mesh plugin
metadata."""
name = "my_mesh"
display_name = "my_display_name"
description = "my mesh is the best of meshes"
tensor_data = test_utils.get_random_mesh(100)
components = 14
with tf.compat.v1.Graph().as_default():
tensor_summary = summary._get_tensor_summary(
name,
display_name,
description,
tensor_data.vertices,
plugin_data_pb2.MeshPluginData.VERTEX,
components,
"",
None,
)
with self.test_session():
proto = self.pb_via_op(tensor_summary)
self.assertEqual("%s_VERTEX" % name, proto.value[0].tag)
self.assertEqual(
metadata.PLUGIN_NAME,
proto.value[0].metadata.plugin_data.plugin_name,
)
self.assertEqual(components,
self.get_components(proto.value[0]))
def test_op(self):
"""Tests merged summary with different types of data."""
name = "my_mesh"
tensor_data = test_utils.get_random_mesh(
100, add_faces=True, add_colors=True
)
config_dict = {"foo": 1}
with tf.compat.v1.Graph().as_default():
tensor_summary = summary.op(
name,
tensor_data.vertices,
faces=tensor_data.faces,
colors=tensor_data.colors,
config_dict=config_dict,
)
with self.test_session() as sess:
proto = self.pb_via_op(tensor_summary)
self.verify_proto(proto, name)
plugin_metadata = metadata.parse_plugin_metadata(
proto.value[0].metadata.plugin_data.content
)
self.assertEqual(
json.dumps(config_dict, sort_keys=True),
plugin_metadata.json_config,
)
def test_step(self):
"""Tests that different components of mesh summary share the same step."""
tensor_data = test_utils.get_random_mesh(100,
add_faces=True,
add_colors=True)
config_dict = {"foo": 1}
events = self.mesh_events('a',
tensor_data.vertices,
faces=tensor_data.faces,
colors=tensor_data.colors,
config_dict=config_dict,
step=333)
self.assertEqual(333, events[0].step)
self.assertEqual(333, events[1].step)
self.assertEqual(333, events[2].step)
def test_pb(self):
"""Tests ProtoBuf interface."""
name = "my_mesh"
tensor_data = test_utils.get_random_mesh(100,
add_faces=True,
add_colors=True)
config_dict = {"foo": 1}
proto = summary.mesh_pb(name,
tensor_data.vertices,
faces=tensor_data.faces,
colors=tensor_data.colors,
config_dict=config_dict)
plugin_metadata = metadata.parse_plugin_metadata(
proto.value[0].metadata.plugin_data.content)
self.assertEqual(json.dumps(config_dict, sort_keys=True),
plugin_metadata.json_config)
def test_pb(self):
"""Tests merged summary protobuf with different types of data."""
name = "my_mesh"
tensor_data = test_utils.get_random_mesh(100,
add_faces=True,
add_colors=True)
config_dict = {"foo": 1}
proto = summary.pb(name,
tensor_data.vertices,
faces=tensor_data.faces,
colors=tensor_data.colors,
config_dict=config_dict)
self.verify_proto(proto, name)
plugin_metadata = metadata.parse_plugin_metadata(
proto.value[0].metadata.plugin_data.content)
self.assertEqual(json.dumps(config_dict, sort_keys=True),
plugin_metadata.json_config)
def setUp(self):
# We use numpy.random to generate meshes. We seed to avoid non-determinism
# in this test.
np.random.seed(17)
# Log dir to save temp events into.
self.log_dir = self.get_temp_dir()
# Create mesh summary.
with tf.compat.v1.Graph().as_default():
tf_placeholder = tf.compat.v1.placeholder
sess = tf.compat.v1.Session()
point_cloud = test_utils.get_random_mesh(1000)
point_cloud_vertices = tf_placeholder(tf.float32,
point_cloud.vertices.shape)
mesh_no_color = test_utils.get_random_mesh(2000, add_faces=True)
mesh_no_color_extended = test_utils.get_random_mesh(2500,
add_faces=True)
mesh_no_color_vertices = tf_placeholder(tf.float32, [1, None, 3])
mesh_no_color_faces = tf_placeholder(tf.int32, [1, None, 3])
mesh_color = test_utils.get_random_mesh(3000,
add_faces=True,
add_colors=True)
mesh_color_vertices = tf_placeholder(tf.float32,
mesh_color.vertices.shape)
mesh_color_faces = tf_placeholder(tf.int32, mesh_color.faces.shape)
mesh_color_colors = tf_placeholder(tf.uint8,
mesh_color.colors.shape)
self.data = [
point_cloud, mesh_no_color, mesh_no_color_extended, mesh_color
]
# In case when name is present and display_name is not, we will reuse name
# as display_name. Summaries below intended to test both cases.
self.names = ["point_cloud", "mesh_no_color", "mesh_color"]
summary.op(self.names[0],
point_cloud_vertices,
description="just point cloud")
summary.op(self.names[1],
mesh_no_color_vertices,
faces=mesh_no_color_faces,
display_name="name_to_display_in_ui",
description="beautiful mesh in grayscale")
summary.op(self.names[2],
mesh_color_vertices,
faces=mesh_color_faces,
colors=mesh_color_colors,
description="mesh with random colors")
merged_summary_op = tf.compat.v1.summary.merge_all()
self.runs = ["bar"]
self.steps = 20
bar_directory = os.path.join(self.log_dir, self.runs[0])
with tensorboard_test_util.FileWriterCache.get(
bar_directory) as writer:
writer.add_graph(sess.graph)
for step in range(self.steps):
# Alternate between two random meshes with different number of
# vertices.
no_color = mesh_no_color if step % 2 == 0 else mesh_no_color_extended
with patch.object(time, 'time', return_value=step):
writer.add_summary(sess.run(merged_summary_op,
feed_dict={
point_cloud_vertices:
point_cloud.vertices,
mesh_no_color_vertices:
no_color.vertices,
mesh_no_color_faces:
no_color.faces,
mesh_color_vertices:
mesh_color.vertices,
mesh_color_faces:
mesh_color.faces,
mesh_color_colors:
mesh_color.colors,
}),
global_step=step)
# Start a server that will receive requests.
self.multiplexer = event_multiplexer.EventMultiplexer({
"bar":
bar_directory,
})
self.context = base_plugin.TBContext(logdir=self.log_dir,
multiplexer=self.multiplexer)
self.plugin = mesh_plugin.MeshPlugin(self.context)
# Wait until after plugin construction to reload the multiplexer because the
# plugin caches data from the multiplexer upon construction and this affects
# logic tested later down.
# TODO(https://github.com/tensorflow/tensorboard/issues/2579): Eliminate the
# caching of data at construction time and move this Reload() up to just
# after the multiplexer is created.
self.multiplexer.Reload()
wsgi_app = application.TensorBoardWSGI([self.plugin])
self.server = werkzeug_test.Client(wsgi_app, wrappers.BaseResponse)
self.routes = self.plugin.get_plugin_apps()
def setUp(self):
# We use numpy.random to generate meshes. We seed to avoid non-determinism
# in this test.
np.random.seed(17)
# Log dir to save temp events into.
self.log_dir = self.get_temp_dir()
# Create mesh summary.
tf.compat.v1.reset_default_graph()
sess = tf.compat.v1.Session()
point_cloud = test_utils.get_random_mesh(1000)
point_cloud_vertices = tf.compat.v1.placeholder(tf.float32,
point_cloud.vertices.shape)
mesh_no_color = test_utils.get_random_mesh(2000, add_faces=True)
mesh_no_color_vertices = tf.compat.v1.placeholder(
tf.float32, mesh_no_color.vertices.shape)
mesh_no_color_faces = tf.compat.v1.placeholder(tf.int32,
mesh_no_color.faces.shape)
mesh_color = test_utils.get_random_mesh(
3000, add_faces=True, add_colors=True)
mesh_color_vertices = tf.compat.v1.placeholder(tf.float32,
mesh_color.vertices.shape)
mesh_color_faces = tf.compat.v1.placeholder(tf.int32,
mesh_color.faces.shape)
mesh_color_colors = tf.compat.v1.placeholder(tf.uint8,
mesh_color.colors.shape)
self.data = [point_cloud, mesh_no_color, mesh_color]
# In case when name is present and display_name is not, we will reuse name
# as display_name. Summaries below intended to test both cases.
self.names = ["point_cloud", "mesh_no_color", "mesh_color"]
summary.op(
self.names[0],
point_cloud_vertices,
description="just point cloud")
summary.op(
self.names[1],
mesh_no_color_vertices,
faces=mesh_no_color_faces,
display_name="name_to_display_in_ui",
description="beautiful mesh in grayscale")
summary.op(
self.names[2],
mesh_color_vertices,
faces=mesh_color_faces,
colors=mesh_color_colors,
description="mesh with random colors")
merged_summary_op = tf.compat.v1.summary.merge_all()
self.runs = ["bar"]
self.steps = 20
bar_directory = os.path.join(self.log_dir, self.runs[0])
with tensorboard_test_util.FileWriterCache.get(bar_directory) as writer:
writer.add_graph(sess.graph)
for step in range(self.steps):
writer.add_summary(
sess.run(
merged_summary_op,
feed_dict={
point_cloud_vertices: point_cloud.vertices,
mesh_no_color_vertices: mesh_no_color.vertices,
mesh_no_color_faces: mesh_no_color.faces,
mesh_color_vertices: mesh_color.vertices,
mesh_color_faces: mesh_color.faces,
mesh_color_colors: mesh_color.colors,
}),
global_step=step)
# Start a server that will receive requests.
self.multiplexer = event_multiplexer.EventMultiplexer({
"bar": bar_directory,
})
self.context = base_plugin.TBContext(
logdir=self.log_dir, multiplexer=self.multiplexer)
self.plugin = mesh_plugin.MeshPlugin(self.context)
wsgi_app = application.TensorBoardWSGIApp(
self.log_dir, [self.plugin],
self.multiplexer,
reload_interval=0,
path_prefix="")
self.server = werkzeug_test.Client(wsgi_app, wrappers.BaseResponse)
self.multiplexer.Reload()
self.routes = self.plugin.get_plugin_apps()
