def run_main():
"""Initializes flags and calls main()."""
program.setup_environment()
if getattr(tf, '__version__', 'stub') == 'stub':
# Unless the user has explicitly requested running without TensorFlow by setting the
# TENSORBOARD_NO_TF environment variable, we check for TensorFlow here so that if it's
# missing we generate a clear and immediate error rather than partial functionality.
# TODO(#2027): Remove environment check once we have placeholder UI
if os.getenv('TENSORBOARD_NO_TF') is None:
import tensorflow # pylint: disable=unused-import
logger.warn(
"TensorFlow installation not found - running with reduced feature set."
)
tensorboard = program.TensorBoard(
default.get_plugins(), program.get_default_assets_zip_provider())
try:
from absl import app
# Import this to check that app.run() will accept the flags_parser argument.
from absl.flags import argparse_flags
app.run(tensorboard.main, flags_parser=tensorboard.configure)
raise AssertionError("absl.app.run() shouldn't return")
except ImportError:
pass
except base_plugin.FlagsError as e:
print("Error: %s" % e, file=sys.stderr)
sys.exit(1)
tensorboard.configure(sys.argv)
sys.exit(tensorboard.main())
def run_main():
"""Initializes flags and calls main()."""
program.setup_environment()
if getattr(tf, '__version__', 'stub') == 'stub':
print(
"TensorFlow installation not found - running with reduced feature set.",
file=sys.stderr)
tensorboard = program.TensorBoard(
default.get_plugins() + default.get_dynamic_plugins(),
program.get_default_assets_zip_provider(),
subcommands=[uploader_main.UploaderSubcommand()])
try:
from absl import app
# Import this to check that app.run() will accept the flags_parser argument.
from absl.flags import argparse_flags
app.run(tensorboard.main, flags_parser=tensorboard.configure)
raise AssertionError("absl.app.run() shouldn't return")
except ImportError:
pass
except base_plugin.FlagsError as e:
print("Error: %s" % e, file=sys.stderr)
sys.exit(1)
tensorboard.configure(sys.argv)
sys.exit(tensorboard.main())
def start_tf_board(client: skein.ApplicationClient,
experiment: Experiment = None):
thread = None
if experiment:
model_dir = experiment.estimator.config.model_dir
else:
model_dir = os.environ.get('TF_BOARD_MODEL_DIR', None)
task = cluster.get_task()
os.environ['GCS_READ_CACHE_DISABLED'] = '1'
os.environ['PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION'] = 'cpp'
os.environ['PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION_VERSION'] = '2'
try:
program.setup_environment()
tensorboard = program.TensorBoard(default.get_plugins(),
default.get_assets_zip_provider())
with _internal.reserve_sock_addr() as (h, p):
tensorboard_url = f"http://{h}:{p}"
argv = ['tensorboard', f"--logdir={model_dir}",
f"--port={p}"]
# Append more arguments if needed.
if 'TF_BOARD_EXTRA_ARGS' in os.environ:
argv += os.environ['TF_BOARD_EXTRA_ARGS'].split(' ')
tensorboard.configure(argv)
tensorboard.launch()
event.url_event(client, task, f"Tensorboard is listening at {tensorboard_url}")
thread = [t for t in threading.enumerate() if t.name == 'TensorBoard'][0]
except Exception as e:
event.stop_event(client, task, e)
return thread
def run_main():
program.setup_environment()
tensorboard = program.TensorBoard()
try:
from absl import app
from absl.flags import argparse_flags
app.run(tensorboard.main, flags_parser=tensorboard.configure)
raise AssertionError("absl.app.run() shouldn't return")
except ImportError:
pass
tensorboard.configure(sys.argv)
sys.exit(tensorboard.main())
def run_main():
"""Initializes flags and calls main()."""
program.setup_environment()
tensorboard = program.TensorBoard(default.get_plugins(),
default.get_assets_zip_provider())
try:
from absl import app
app.run(tensorboard.main, flags_parser=tensorboard.configure)
raise AssertionError("absl.app.run() shouldn't return")
except ImportError:
pass
tensorboard.configure(sys.argv)
sys.exit(tensorboard.main())
def run_main():
"""Initializes flags and calls main()."""
program.setup_environment()
tensorboard = program.TensorBoard(get_notf_plugins(),
program.get_default_assets_zip_provider())
try:
from absl import app
# Import this to check that app.run() will accept the flags_parser argument.
from absl.flags import argparse_flags
app.run(tensorboard.main, flags_parser=tensorboard.configure)
raise AssertionError("absl.app.run() shouldn't return")
except ImportError:
pass
tensorboard.configure(sys.argv)
sys.exit(tensorboard.main())
def run_main():
"""Initializes flags and calls main()."""
program.setup_environment()
tensorboard = program.TensorBoard(default.get_plugins(),
default.get_assets_zip_provider())
try:
from absl import app
# Import this to check that app.run() will accept the flags_parser argument.
from absl.flags import argparse_flags
app.run(tensorboard.main, flags_parser=tensorboard.configure)
raise AssertionError("absl.app.run() shouldn't return")
except ImportError:
pass
tensorboard.configure(sys.argv)
sys.exit(tensorboard.main())
def run(self):
'''Launch the tensorboard.
Note that this method would not block the main thread, we
suggest to use launch() instead of this when you do not need
to work with subthread.
'''
program.setup_environment()
# Remove http messages
log = logging.getLogger('werkzeug').setLevel(logging.ERROR)
# Start tensorboard server
_tb = program.TensorBoard(
default.get_plugins(),
program.get_default_assets_zip_provider())
_tb.configure(argv=self.__collect_argvs())
url = _tb.launch()
print('TensorBoard at {0}, working on path: {1}.'.format(url, self.log_dir))
def run_main():
"""Initializes flags and calls main()."""
program.setup_environment()
server = program.TensorBoard(default.PLUGIN_LOADERS,
default.get_assets_zip_provider())
server.configure(sys.argv[1:])
try:
from absl import app
app.run(server.main, sys.argv[:1] + server.unparsed_argv)
raise AssertionError("absl.app.run() shouldn't return")
except ImportError:
pass
if server.unparsed_argv:
sys.stderr.write('Unknown flags: %s\nPass --help for help.\n' %
(server.unparsed_argv, ))
sys.exit(1)
sys.exit(server.main())
def start_tf_board(client: skein.ApplicationClient, tf_board_model_dir: str):
task = cluster.get_task()
os.environ['GCS_READ_CACHE_DISABLED'] = '1'
os.environ['PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION'] = 'cpp'
os.environ['PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION_VERSION'] = '2'
try:
program.setup_environment()
tensorboard = program.TensorBoard()
with _internal.reserve_sock_addr() as (h, p):
tensorboard_url = f"http://{h}:{p}"
argv = ['tensorboard', f"--logdir={tf_board_model_dir}",
f"--port={p}"]
tb_extra_args = os.getenv('TB_EXTRA_ARGS', "")
if tb_extra_args:
argv += tb_extra_args.split(' ')
tensorboard.configure(argv)
tensorboard.launch()
event.start_event(client, task)
event.url_event(client, task, f"{tensorboard_url}")
except Exception as e:
_logger.error("Cannot start tensorboard", e)
event.stop_event(client, task, e)