def main(unused_argv=None):
if FLAGS.debug:
logging.set_verbosity(logging.DEBUG)
if not FLAGS.logdir:
logging.error('A logdir must be specified. Run `tensorboard --help` for '
'details and examples.')
return -1
if FLAGS.debug:
logging.info('Starting TensorBoard in directory %s', os.getcwd())
path_to_run = ParseEventFilesFlag(FLAGS.logdir)
multiplexer = event_multiplexer.AutoloadingMultiplexer(
path_to_run=path_to_run, interval_secs=60,
size_guidance=TENSORBOARD_SIZE_GUIDANCE)
multiplexer.AutoUpdate(interval=30)
factory = functools.partial(tensorboard_handler.TensorboardHandler,
multiplexer)
try:
server = ThreadedHTTPServer((FLAGS.host, FLAGS.port), factory)
except socket.error:
logging.error('Tried to connect to port %d, but that address is in use.',
FLAGS.port)
return -2
status_bar.SetupStatusBarInsideGoogle('TensorBoard', FLAGS.port)
print('Starting TensorBoard on port %d' % FLAGS.port)
print('(You can navigate to http://localhost:%d)' % FLAGS.port)
server.serve_forever()
def get_global_step(graph=None):
"""Get the global step tensor.
The global step tensor must be an integer variable. We first try to find it
in the collection `GLOBAL_STEP`, or by name `global_step:0`.
Args:
graph: The graph to find the global step in. If missing, use default graph.
Returns:
The global step variable, or `None` if none was found.
Raises:
TypeError: If the global step tensor has a non-integer type, or if it is not
a `Variable`.
"""
graph = ops.get_default_graph() if graph is None else graph
global_step_tensor = None
global_step_tensors = graph.get_collection(ops.GraphKeys.GLOBAL_STEP)
if len(global_step_tensors) == 1:
global_step_tensor = global_step_tensors[0]
elif not global_step_tensors:
try:
global_step_tensor = graph.get_tensor_by_name('global_step:0')
except KeyError:
return None
else:
logging.error('Multiple tensors in global_step collection.')
return None
assert_global_step(global_step_tensor)
return global_step_tensor
def get_global_step(graph=None):
"""Get the global step tensor.
The global step tensor must be an integer variable. We first try to find it
in the collection `GLOBAL_STEP`, or by name `global_step:0`.
Args:
graph: The graph to find the global step in. If missing, use default graph.
Returns:
The global step variable, or `None` if none was found.
Raises:
TypeError: If the global step tensor has a non-integer type, or if it is not
a `Variable`.
"""
graph = ops.get_default_graph() if graph is None else graph
global_step_tensor = None
global_step_tensors = graph.get_collection(ops.GraphKeys.GLOBAL_STEP)
if len(global_step_tensors) == 1:
global_step_tensor = global_step_tensors[0]
elif not global_step_tensors:
try:
global_step_tensor = graph.get_tensor_by_name('global_step:0')
except KeyError:
return None
else:
logging.error('Multiple tensors in global_step collection.')
return None
assert_global_step(global_step_tensor)
return global_step_tensor
def __exit__(self, exec_type, exec_value, exec_tb):
if exec_type is errors.OpError:
logging.error('Session closing due to OpError: %s', (exec_value, ))
for context_manager in reversed(self._context_managers):
context_manager.__exit__(exec_type, exec_value, exec_tb)
self.close()
def __exit__(self, exec_type, exec_value, exec_tb):
if exec_type is errors.OpError:
logging.error('Session closing due to OpError: %s', (exec_value,))
for context_manager in reversed(self._context_managers):
context_manager.__exit__(exec_type, exec_value, exec_tb)
self.close()
def main(unused_argv=None):
if FLAGS.debug:
logging.set_verbosity(logging.DEBUG)
logging.info('TensorBoard is in debug mode.')
if not FLAGS.logdir:
logging.error(
'A logdir must be specified. Run `tensorboard --help` for '
'details and examples.')
return -1
logging.info('Starting TensorBoard in directory %s', os.getcwd())
path_to_run = ParseEventFilesFlag(FLAGS.logdir)
logging.info('TensorBoard path_to_run is: %s', path_to_run)
multiplexer = event_multiplexer.EventMultiplexer(
size_guidance=TENSORBOARD_SIZE_GUIDANCE)
def _Load():
start = time.time()
for (path, name) in six.iteritems(path_to_run):
multiplexer.AddRunsFromDirectory(path, name)
multiplexer.Reload()
duration = time.time() - start
logging.info('Multiplexer done loading. Load took %0.1f secs',
duration)
t = threading.Timer(LOAD_INTERVAL, _Load)
t.daemon = True
t.start()
t = threading.Timer(0, _Load)
t.daemon = True
t.start()
factory = functools.partial(tensorboard_handler.TensorboardHandler,
multiplexer)
try:
server = ThreadedHTTPServer((FLAGS.host, FLAGS.port), factory)
except socket.error:
logging.error(
'Tried to connect to port %d, but that address is in use.',
FLAGS.port)
return -2
try:
tag = resource_loader.load_resource('tensorboard/TAG').strip()
logging.info('TensorBoard is tag: %s', tag)
except IOError:
logging.warning('Unable to read TensorBoard tag')
tag = ''
status_bar.SetupStatusBarInsideGoogle('TensorBoard %s' % tag, FLAGS.port)
print('Starting TensorBoard %s on port %d' % (tag, FLAGS.port))
print('(You can navigate to http://%s:%d)' % (FLAGS.host, FLAGS.port))
server.serve_forever()
def main(unused_argv=None):
if FLAGS.debug:
logging.set_verbosity(logging.DEBUG)
logging.info('TensorBoard is in debug mode.')
if not FLAGS.logdir:
logging.error('A logdir must be specified. Run `tensorboard --help` for '
'details and examples.')
return -1
logging.info('Starting TensorBoard in directory %s', os.getcwd())
path_to_run = ParseEventFilesFlag(FLAGS.logdir)
logging.info('TensorBoard path_to_run is: %s', path_to_run)
multiplexer = event_multiplexer.EventMultiplexer(
size_guidance=TENSORBOARD_SIZE_GUIDANCE)
# Ensure the Multiplexer initializes in a loaded state before it adds runs
# So it can handle HTTP requests while runs are loading
multiplexer.Reload()
def _Load():
start = time.time()
for (path, name) in six.iteritems(path_to_run):
multiplexer.AddRunsFromDirectory(path, name)
multiplexer.Reload()
duration = time.time() - start
logging.info('Multiplexer done loading. Load took %0.1f secs', duration)
t = threading.Timer(LOAD_INTERVAL, _Load)
t.daemon = True
t.start()
t = threading.Timer(0, _Load)
t.daemon = True
t.start()
factory = functools.partial(tensorboard_handler.TensorboardHandler,
multiplexer)
try:
server = ThreadedHTTPServer((FLAGS.host, FLAGS.port), factory)
except socket.error:
logging.error('Tried to connect to port %d, but that address is in use.',
FLAGS.port)
return -2
try:
tag = resource_loader.load_resource('tensorboard/TAG').strip()
logging.info('TensorBoard is tag: %s', tag)
except IOError:
logging.warning('Unable to read TensorBoard tag')
tag = ''
status_bar.SetupStatusBarInsideGoogle('TensorBoard %s' % tag, FLAGS.port)
print('Starting TensorBoard %s on port %d' % (tag, FLAGS.port))
print('(You can navigate to http://%s:%d)' % (FLAGS.host, FLAGS.port))
server.serve_forever()
def _import_meta_graph_def(meta_graph_def):
"""Recreates a Graph saved in a a `MetaGraphDef` proto.
This function adds all the nodes from the meta graph def proto to the current
graph, recreates all the collections, and returns a saver from saver_def.
Args:
meta_graph_def: `MetaGraphDef` protocol buffer.
Returns:
A saver constructed rom `saver_def` in `meta_graph_def`.
"""
# Gathers the list of nodes we are interested in.
importer.import_graph_def(meta_graph_def.graph_def, name="")
# Restores all the other collections.
for key, col_def in meta_graph_def.collection_def.items():
kind = col_def.WhichOneof("kind")
if kind is None:
logging.error("Cannot identify data type for collection %s. Skipping."
% key)
continue
from_proto = ops.get_from_proto_function(key)
if from_proto:
assert kind == "bytes_list"
proto_type = ops.get_collection_proto_type(key)
for value in col_def.bytes_list.value:
proto = proto_type()
proto.ParseFromString(value)
ops.add_to_collection(key, from_proto(proto))
else:
field = getattr(col_def, kind)
if kind == "node_list":
for value in field.value:
col_op = ops.get_default_graph().as_graph_element(value)
ops.add_to_collection(key, col_op)
elif kind == "int64_list":
# NOTE(opensource): This force conversion is to work around the fact
# that Python2 distinguishes between int and long, while Python3 has
# only int.
for value in field.value:
ops.add_to_collection(key, int(value))
else:
for value in field.value:
ops.add_to_collection(key, value)
if meta_graph_def.HasField("saver_def"):
return Saver(saver_def=meta_graph_def.saver_def)
else:
return Saver()
def CheckIsSupported():
"""Raises an OSError if the system isn't set up for Google Cloud Storage.
Raises:
OSError: If the system hasn't been set up so that TensorBoard can access
Google Cloud Storage. The error's message contains installation
instructions.
"""
try:
subprocess.check_output(['gsutil', 'version'])
except OSError as e:
logging.error('Error while checking for gsutil: %s', e)
raise OSError(
'Unable to execute the gsutil binary, which is required for Google '
'Cloud Storage support. You can find installation instructions at '
'https://goo.gl/sST520')
def _run(self, sess, enqueue_op, coord=None):
"""Execute the enqueue op in a loop, close the queue in case of error.
Args:
sess: A Session.
enqueue_op: The Operation to run.
coord: Optional Coordinator object for reporting errors and checking
for stop conditions.
"""
decremented = False
try:
while True:
if coord and coord.should_stop():
break
try:
sess.run(enqueue_op)
except errors.OutOfRangeError:
# This exception indicates that a queue was closed.
with self._lock:
self._runs -= 1
decremented = True
if self._runs == 0:
try:
sess.run(self._close_op)
except Exception as e:
# Intentionally ignore errors from close_op.
logging.vlog(1, "Ignored exception: %s",
str(e))
return
except Exception as e:
# This catches all other exceptions.
if coord:
coord.request_stop(e)
else:
logging.error("Exception in QueueRunner: %s", str(e))
with self._lock:
self._exceptions_raised.append(e)
raise
finally:
# Make sure we account for all terminations: normal or errors.
if not decremented:
with self._lock:
self._runs -= 1
def _run(self, sess, enqueue_op, coord=None):
"""Execute the enqueue op in a loop, close the queue in case of error.
Args:
sess: A Session.
enqueue_op: The Operation to run.
coord: Optional Coordinator object for reporting errors and checking
for stop conditions.
"""
decremented = False
try:
while True:
if coord and coord.should_stop():
break
try:
sess.run(enqueue_op)
except errors.OutOfRangeError:
# This exception indicates that a queue was closed.
with self._lock:
self._runs -= 1
decremented = True
if self._runs == 0:
try:
sess.run(self._close_op)
except Exception as e:
# Intentionally ignore errors from close_op.
logging.vlog(1, "Ignored exception: %s", str(e))
return
except Exception as e:
# This catches all other exceptions.
if coord:
coord.request_stop(e)
else:
logging.error("Exception in QueueRunner: %s", str(e))
with self._lock:
self._exceptions_raised.append(e)
raise
finally:
# Make sure we account for all terminations: normal or errors.
if not decremented:
with self._lock:
self._runs -= 1
def main(unused_argv=None):
if FLAGS.debug:
logging.set_verbosity(logging.DEBUG)
logging.info('TensorBoard is in debug mode.')
if not FLAGS.logdir:
logging.error(
'A logdir must be specified. Run `tensorboard --help` for '
'details and examples.')
return -1
if FLAGS.debug:
logging.info('Starting TensorBoard in directory %s', os.getcwd())
path_to_run = ParseEventFilesFlag(FLAGS.logdir)
multiplexer = event_multiplexer.AutoloadingMultiplexer(
path_to_run=path_to_run,
interval_secs=60,
size_guidance=TENSORBOARD_SIZE_GUIDANCE)
multiplexer.AutoUpdate(interval=30)
factory = functools.partial(tensorboard_handler.TensorboardHandler,
multiplexer)
try:
server = ThreadedHTTPServer((FLAGS.host, FLAGS.port), factory)
except socket.error:
logging.error(
'Tried to connect to port %d, but that address is in use.',
FLAGS.port)
return -2
try:
tag = resource_loader.load_resource('tensorboard/TAG').strip()
logging.info('TensorBoard is tag: %s', tag)
except IOError:
logging.warning('Unable to read TensorBoard tag')
tag = ''
status_bar.SetupStatusBarInsideGoogle('TensorBoard %s' % tag, FLAGS.port)
print('Starting TensorBoard %s on port %d' % (tag, FLAGS.port))
print('(You can navigate to http://%s:%d)' % (FLAGS.host, FLAGS.port))
server.serve_forever()
def main(unused_argv=None):
# Change current working directory to tensorflow/'s parent directory.
server_root = os.path.join(os.path.dirname(__file__), os.pardir, os.pardir)
os.chdir(server_root)
if FLAGS.debug:
logging.set_verbosity(logging.DEBUG)
if not FLAGS.logdir:
logging.error(
'A logdir must be specified. Run `tensorboard --help` for '
'details and examples.')
return -1
if FLAGS.debug:
logging.info('Starting TensorBoard in directory %s', os.getcwd())
path_to_run = ParseEventFilesFlag(FLAGS.logdir)
multiplexer = event_multiplexer.AutoloadingMultiplexer(
path_to_run=path_to_run,
interval_secs=60,
size_guidance=TENSORBOARD_SIZE_GUIDANCE)
multiplexer.AutoUpdate(interval=30)
factory = functools.partial(tensorboard_handler.TensorboardHandler,
multiplexer)
try:
server = ThreadedHTTPServer((FLAGS.host, FLAGS.port), factory)
except socket.error:
logging.error(
'Tried to connect to port %d, but that address is in use.',
FLAGS.port)
return -2
status_bar.SetupStatusBarInsideGoogle('TensorBoard', FLAGS.port)
print('Starting TensorBoard on port %d' % FLAGS.port)
print('(You can navigate to http://localhost:%d)' % FLAGS.port)
server.serve_forever()
def main(unused_argv=None):
if FLAGS.debug:
logging.set_verbosity(logging.DEBUG)
logging.info("TensorBoard is in debug mode.")
if not FLAGS.logdir:
logging.error("A logdir must be specified. Run `tensorboard --help` for " "details and examples.")
return -1
if FLAGS.debug:
logging.info("Starting TensorBoard in directory %s", os.getcwd())
path_to_run = ParseEventFilesFlag(FLAGS.logdir)
multiplexer = event_multiplexer.AutoloadingMultiplexer(
path_to_run=path_to_run, interval_secs=60, size_guidance=TENSORBOARD_SIZE_GUIDANCE
)
multiplexer.AutoUpdate(interval=30)
factory = functools.partial(tensorboard_handler.TensorboardHandler, multiplexer)
try:
server = ThreadedHTTPServer((FLAGS.host, FLAGS.port), factory)
except socket.error:
logging.error("Tried to connect to port %d, but that address is in use.", FLAGS.port)
return -2
try:
tag = resource_loader.load_resource("tensorboard/TAG").strip()
logging.info("TensorBoard is tag: %s", tag)
except IOError:
logging.warning("Unable to read TensorBoard tag")
tag = ""
status_bar.SetupStatusBarInsideGoogle("TensorBoard %s" % tag, FLAGS.port)
print("Starting TensorBoard %s on port %d" % (tag, FLAGS.port))
print("(You can navigate to http://localhost:%d)" % FLAGS.port)
server.serve_forever()
def main(unused_argv=None):
if FLAGS.debug:
logging.set_verbosity(logging.DEBUG)
logging.info('TensorBoard is in debug mode.')
if not FLAGS.logdir:
msg = ('A logdir must be specified. Run `tensorboard --help` for '
'details and examples.')
logging.error(msg)
print(msg)
return -1
logging.info('Starting TensorBoard in directory %s', os.getcwd())
path_to_run = server.ParseEventFilesSpec(FLAGS.logdir)
logging.info('TensorBoard path_to_run is: %s', path_to_run)
multiplexer = event_multiplexer.EventMultiplexer(
size_guidance=server.TENSORBOARD_SIZE_GUIDANCE,
purge_orphaned_data=FLAGS.purge_orphaned_data)
server.StartMultiplexerReloadingThread(multiplexer, path_to_run,
FLAGS.reload_interval)
try:
tb_server = server.BuildServer(multiplexer, FLAGS.host, FLAGS.port)
except socket.error:
if FLAGS.port == 0:
msg = 'Unable to find any open ports.'
logging.error(msg)
print(msg)
return -2
else:
msg = 'Tried to connect to port %d, but address is in use.' % FLAGS.port
logging.error(msg)
print(msg)
return -3
try:
tag = resource_loader.load_resource('tensorboard/TAG').strip()
logging.info('TensorBoard is tag: %s', tag)
except IOError:
logging.warning('Unable to read TensorBoard tag')
tag = ''
status_bar.SetupStatusBarInsideGoogle('TensorBoard %s' % tag, FLAGS.port)
print('Starting TensorBoard %s on port %d' % (tag, FLAGS.port))
print('(You can navigate to http://%s:%d)' % (FLAGS.host, FLAGS.port))
tb_server.serve_forever()
def main(unused_argv=None):
if FLAGS.debug:
logging.set_verbosity(logging.DEBUG)
logging.info('TensorBoard is in debug mode.')
if not FLAGS.logdir:
msg = ('A logdir must be specified. Run `tensorboard --help` for '
'details and examples.')
logging.error(msg)
print(msg)
return -1
logging.info('Starting TensorBoard in directory %s', os.getcwd())
path_to_run = server.ParseEventFilesSpec(FLAGS.logdir)
logging.info('TensorBoard path_to_run is: %s', path_to_run)
multiplexer = event_multiplexer.EventMultiplexer(
size_guidance=server.TENSORBOARD_SIZE_GUIDANCE,
purge_orphaned_data=FLAGS.purge_orphaned_data)
server.StartMultiplexerReloadingThread(multiplexer, path_to_run,
FLAGS.reload_interval)
try:
tb_server = server.BuildServer(multiplexer, FLAGS.host, FLAGS.port)
except socket.error:
if FLAGS.port == 0:
msg = 'Unable to find any open ports.'
logging.error(msg)
print(msg)
return -2
else:
msg = 'Tried to connect to port %d, but address is in use.' % FLAGS.port
logging.error(msg)
print(msg)
return -3
try:
tag = resource_loader.load_resource('tensorboard/TAG').strip()
logging.info('TensorBoard is tag: %s', tag)
except IOError:
logging.warning('Unable to read TensorBoard tag')
tag = ''
status_bar.SetupStatusBarInsideGoogle('TensorBoard %s' % tag, FLAGS.port)
print('Starting TensorBoard %s on port %d' % (tag, FLAGS.port))
print('(You can navigate to http://%s:%d)' % (FLAGS.host, FLAGS.port))
tb_server.serve_forever()
