def execute(self, server_info, channel):
api_client = export_service_pb2_grpc.TensorBoardExporterServiceStub(
channel)
fieldmask = experiment_pb2.ExperimentMask(
name=True,
description=True,
create_time=True,
update_time=True,
num_runs=True,
num_tags=True,
num_scalars=True,
total_tensor_bytes=True,
total_blob_bytes=True,
)
gen = exporter_lib.list_experiments(api_client, fieldmask=fieldmask)
count = 0
if self.json:
formatter = formatters.JsonFormatter()
else:
formatter = formatters.ReadableFormatter()
for experiment in gen:
count += 1
experiment_id = experiment.experiment_id
url = server_info_lib.experiment_url(server_info, experiment_id)
print(formatter.format_experiment(experiment, url))
sys.stdout.flush()
if not count:
sys.stderr.write(
"No experiments. Use `tensorboard dev upload` to get started.\n"
)
else:
sys.stderr.write("Total: %d experiment(s)\n" % count)
sys.stderr.flush()
def _create_mock_api_client():
# Create a stub instance (using a test channel) in order to derive a mock
# from it with autospec enabled. Mocking TensorBoardExporterServiceStub
# itself doesn't work with autospec because grpc constructs stubs via
# metaclassing.
test_channel = grpc_testing.channel(service_descriptors=[],
time=grpc_testing.strict_real_time())
stub = export_service_pb2_grpc.TensorBoardExporterServiceStub(test_channel)
mock_api_client = mock.create_autospec(stub)
return mock_api_client
def get_api_client(api_endpoint=None):
server_info = _get_server_info(api_endpoint=api_endpoint)
_handle_server_info(server_info)
channel_creds = grpc.ssl_channel_credentials()
credentials = auth.CredentialsStore().read_credentials()
if credentials:
channel_creds = grpc.composite_channel_credentials(
channel_creds, auth.id_token_call_credentials(credentials))
channel = grpc.secure_channel(server_info.api_server.endpoint,
channel_creds)
return export_service_pb2_grpc.TensorBoardExporterServiceStub(channel)
def execute(self, channel):
api_client = export_service_pb2_grpc.TensorBoardExporterServiceStub(channel)
outdir = self.output_dir
try:
exporter = exporter_lib.TensorBoardExporter(api_client, outdir)
except exporter_lib.OutputDirectoryExistsError:
msg = 'Output directory already exists: %r' % outdir
raise base_plugin.FlagsError(msg)
num_experiments = 0
for experiment_id in exporter.export():
num_experiments += 1
print('Downloaded experiment %s' % experiment_id)
print('Done. Downloaded %d experiments to: %s' % (num_experiments, outdir))
def execute(self, server_info, channel):
api_client = export_service_pb2_grpc.TensorBoardExporterServiceStub(
channel)
gen = exporter_lib.list_experiments(api_client)
count = 0
for experiment_id in gen:
count += 1
url = server_info_lib.experiment_url(server_info, experiment_id)
print(url)
sys.stdout.flush()
if not count:
sys.stderr.write(
'No experiments. Use `tensorboard dev upload` to get started.\n'
)
else:
sys.stderr.write('Total: %d experiment(s)\n' % count)
sys.stderr.flush()
def execute(self, channel):
api_client = export_service_pb2_grpc.TensorBoardExporterServiceStub(
channel)
gen = exporter_lib.list_experiments(api_client)
count = 0
for experiment_id in gen:
count += 1
# TODO(@wchargin): Once #2879 is in, remove this hard-coded URL pattern.
url = 'https://tensorboard.dev/experiment/%s/' % experiment_id
print(url)
sys.stdout.flush()
if not count:
sys.stderr.write(
'No experiments. Use `tensorboard dev upload` to get started.\n'
)
else:
sys.stderr.write('Total: %d experiment(s)\n' % count)
sys.stderr.flush()
def execute(self, server_info, channel):
api_client = export_service_pb2_grpc.TensorBoardExporterServiceStub(
channel
)
fieldmask = experiment_pb2.ExperimentMask(
create_time=True,
update_time=True,
num_scalars=True,
num_runs=True,
num_tags=True,
)
gen = exporter_lib.list_experiments(api_client, fieldmask=fieldmask)
count = 0
for experiment in gen:
count += 1
if not isinstance(experiment, experiment_pb2.Experiment):
url = server_info_lib.experiment_url(server_info, experiment)
print(url)
continue
experiment_id = experiment.experiment_id
url = server_info_lib.experiment_url(server_info, experiment_id)
print(url)
data = [
("Name", experiment.name or "[No Name]"),
("Description", experiment.description or "[No Description]"),
("Id", experiment.experiment_id),
("Created", util.format_time(experiment.create_time)),
("Updated", util.format_time(experiment.update_time)),
("Scalars", str(experiment.num_scalars)),
("Runs", str(experiment.num_runs)),
("Tags", str(experiment.num_tags)),
]
for (name, value) in data:
print("\t%s %s" % (name.ljust(12), value))
sys.stdout.flush()
if not count:
sys.stderr.write(
"No experiments. Use `tensorboard dev upload` to get started.\n"
)
else:
sys.stderr.write("Total: %d experiment(s)\n" % count)
sys.stderr.flush()
def execute(self, server_info, channel):
api_client = export_service_pb2_grpc.TensorBoardExporterServiceStub(
channel)
outdir = self.output_dir
try:
exporter = exporter_lib.TensorBoardExporter(api_client, outdir)
except exporter_lib.OutputDirectoryExistsError:
msg = "Output directory already exists: %r" % outdir
raise base_plugin.FlagsError(msg)
num_experiments = 0
try:
for experiment_id in exporter.export():
num_experiments += 1
print("Downloaded experiment %s" % experiment_id)
except exporter_lib.GrpcTimeoutException as e:
print(
"\nUploader has failed because of a timeout error. Please reach "
"out via e-mail to [email protected] to get help "
"completing your export of experiment %s." % e.experiment_id)
print("Done. Downloaded %d experiments to: %s" %
(num_experiments, outdir))
def execute(self, server_info, channel):
api_client = export_service_pb2_grpc.TensorBoardExporterServiceStub(
channel)
fieldmask = export_service_pb2.ExperimentMask(
create_time=True,
update_time=True,
num_scalars=True,
num_runs=True,
num_tags=True,
)
gen = exporter_lib.list_experiments(api_client, fieldmask=fieldmask)
count = 0
for experiment in gen:
count += 1
if not isinstance(experiment, export_service_pb2.Experiment):
url = server_info_lib.experiment_url(server_info, experiment)
print(url)
continue
experiment_id = experiment.experiment_id
url = server_info_lib.experiment_url(server_info, experiment_id)
print(url)
data = [
('Id', experiment.experiment_id),
('Created', util.format_time(experiment.create_time)),
('Updated', util.format_time(experiment.update_time)),
('Scalars', str(experiment.num_scalars)),
('Runs', str(experiment.num_runs)),
('Tags', str(experiment.num_tags)),
]
for (name, value) in data:
print('\t%s %s' % (name.ljust(10), value))
sys.stdout.flush()
if not count:
sys.stderr.write(
'No experiments. Use `tensorboard dev upload` to get started.\n'
)
else:
sys.stderr.write('Total: %d experiment(s)\n' % count)
sys.stderr.flush()
