def testSetLayout(self):
layout_proto_to_write = layout_pb2.Layout(category=[
layout_pb2.Category(
title='mean biases',
chart=[
layout_pb2.Chart(
title='mean layer biases',
multiline=layout_pb2.MultilineChartContent(
tag=[r'mean/layer\d+/biases'], )),
]),
layout_pb2.Category(
title='std weights',
chart=[
layout_pb2.Chart(
title='stddev layer weights',
multiline=layout_pb2.MultilineChartContent(
tag=[r'stddev/layer\d+/weights'], )),
]),
layout_pb2.Category(
title='cross entropy ... and maybe some other values',
chart=[
layout_pb2.Chart(
title='cross entropy',
multiline=layout_pb2.MultilineChartContent(
tag=[r'cross entropy'], )),
layout_pb2.Chart(
title='accuracy',
margin=layout_pb2.MarginChartContent(series=[
layout_pb2.MarginChartContent.Series(
value='accuracy',
lower='accuracy_lower_margin',
upper='accuracy_upper_margin')
])),
layout_pb2.Chart(
title='max layer weights',
multiline=layout_pb2.MultilineChartContent(
tag=[r'max/layer1/.*', r'max/layer2/.*'], )),
],
closed=True)
])
# Write the data as a summary for the '.' run.
with tf.Session() as s, tf.summary.FileWriter(self.logdir) as writer:
writer.add_summary(s.run(summary.op(layout_proto_to_write)))
# Read the data from disk.
multiplexer = event_multiplexer.EventMultiplexer()
multiplexer.AddRunsFromDirectory(self.logdir)
multiplexer.Reload()
tensor_events = multiplexer.Tensors('.', metadata.CONFIG_SUMMARY_TAG)
self.assertEqual(1, len(tensor_events))
# Parse the data.
string_array = tf.make_ndarray(tensor_events[0].tensor_proto)
content = np.asscalar(string_array)
layout_proto_from_disk = layout_pb2.Layout()
layout_proto_from_disk.ParseFromString(tf.compat.as_bytes(content))
# Verify the content.
self.assertProtoEquals(layout_proto_to_write, layout_proto_from_disk)
def testSetLayout(self):
layout_proto_to_write = layout_pb2.Layout(
category=[
layout_pb2.Category(
title='mean biases',
chart=[
layout_pb2.Chart(
title='mean layer biases',
multiline=layout_pb2.MultilineChartContent(
tag=[r'mean/layer\d+/biases'],
)),
]),
layout_pb2.Category(
title='std weights',
chart=[
layout_pb2.Chart(
title='stddev layer weights',
multiline=layout_pb2.MultilineChartContent(
tag=[r'stddev/layer\d+/weights'],
)),
]),
layout_pb2.Category(
title='cross entropy ... and maybe some other values',
chart=[
layout_pb2.Chart(
title='cross entropy',
multiline=layout_pb2.MultilineChartContent(
tag=[r'cross entropy'],
)),
layout_pb2.Chart(
title='accuracy',
margin=layout_pb2.MarginChartContent(
series=[
layout_pb2.MarginChartContent.Series(
value='accuracy',
lower='accuracy_lower_margin',
upper='accuracy_upper_margin')
]
)),
layout_pb2.Chart(
title='max layer weights',
multiline=layout_pb2.MultilineChartContent(
tag=[r'max/layer1/.*', r'max/layer2/.*'],
)),
],
closed=True)
])
# Write the data as a summary for the '.' run.
with tf.Session() as s, tf.summary.FileWriter(self.logdir) as writer:
writer.add_summary(s.run(summary.op(layout_proto_to_write)))
# Read the data from disk.
multiplexer = event_multiplexer.EventMultiplexer()
multiplexer.AddRunsFromDirectory(self.logdir)
multiplexer.Reload()
tensor_events = multiplexer.Tensors('.', metadata.CONFIG_SUMMARY_TAG)
self.assertEqual(1, len(tensor_events))
# Parse the data.
string_array = tf.make_ndarray(tensor_events[0].tensor_proto)
content = np.asscalar(string_array)
layout_proto_from_disk = layout_pb2.Layout()
layout_proto_from_disk.ParseFromString(tf.compat.as_bytes(content))
# Verify the content.
self.assertProtoEquals(layout_proto_to_write, layout_proto_from_disk)