def list(self):
count = 0
for project in iter(Project(self.ctx).list()):
self.ctx.log(project.get('name'))
count += 1
self.ctx.log('%s Project(s) listed' % str(count))
return {'projects': Project(self.ctx).list()}
def __init__(self, ctx):
self.ctx = ctx
def print_(*args, **kwargs):
print(*args, **kwargs)
self.ctx.log = print_
self.dataset = None
self.model_id = None
self.project = Project(self.ctx, self.ctx.config.get('name', None))
def _get_project(self, autocreate):
project_name = self.ctx.config.get('name', None)
if project_name is None:
raise AugerException(
'Please specify project name in auger.yaml/name...')
project = Project(self.ctx, project_name)
project_properties = project.properties()
if project_properties is None:
if autocreate:
self.ctx.log('Can\'t find project %s on the Auger Cloud. '
'Creating...' % project_name)
project.create()
else:
raise AugerException('Can\'t find project %s' % project_name)
return project
def _setup_op(self, name, verify_project=True):
old_name = self.ctx.config.get('name', None)
if name is None:
name = old_name
if name is None:
raise AugerException('Please specify Project name...')
project = Project(self.ctx, name)
if verify_project and not project.is_exists:
raise AugerException('Project %s doesn\'t exists...' % name)
return old_name, name, project
class ExampleApp():
def __init__(self, ctx):
self.ctx = ctx
def print_(*args, **kwargs):
print(*args, **kwargs)
self.ctx.log = print_
self.dataset = None
self.model_id = None
self.project = Project(self.ctx, self.ctx.config.get('name', None))
def _get_datasets(self):
"""return list of existing datasets in the Aguer Cloud"""
dataset_list = []
for dataset in iter(DataSet(self.ctx, self.project).list()):
dataset_list.append(dataset['name'])
return dataset_list
def _start_experiment(self, experiment_name):
experiment = Experiment(self.ctx, self.dataset, experiment_name)
experiment_name, session_id = \
experiment.start()
AugerConfig(self.ctx).set_experiment(experiment_name, session_id)
return experiment, session_id
def prepare_dataset(self):
"""check whether dataset selected, if not, select or create one"""
self.ctx.log("Checking dataset...")
selected = self.ctx.config.get('dataset', None)
if selected is None:
if DATASET_NAME in self._get_datasets():
# try to select existing
AugerConfig(self.ctx).set_data_set(DATASET_NAME,
'').set_experiment(None)
self.dataset = DataSet(self.ctx, self.project, DATASET_NAME)
else:
# or create new
self.ctx.log("No dataset found, creating the first one...")
source = self.ctx.config.get('source', None)
dataset = DataSet(self.ctx, self.project).create(source)
AugerConfig(self.ctx).set_data_set(dataset.name,
source).set_experiment(None)
self.dataset = DataSet(self.ctx, self.project, dataset.name)
else:
self.dataset = DataSet(self.ctx, self.project, selected)
self.ctx.log("Currently selected: %s" % selected)
def run_experiment(self):
experiment_name = self.ctx.config.get('experiment/name', None)
# run_id = self.ctx.config.get(
# 'experiment/experiment_session_id', None)
# if run_id is None or experiment_name is None:
# if no experiment ran:
# run_id = self._start_experiment(experiment_name)
self.experiment, run_id = self._start_experiment(experiment_name)
# else:
# # if experiment exists, (start if needed) and wait for it
# session_api = AugerExperimentSessionApi(
# self.ctx, None, None, run_id)
# status = session_api.properties().get('status')
# self.ctx.log('Experiment status is %s' % status)
# # available choices are:
# # [preprocess, started, completed, interrupted]
# if status not in ('preprocess', 'started'):
# run_id = self._start_experiment(experiment_name)
# wait for experiment to stop
self.ctx.log("waiting for experiment %s to finish" % experiment_name)
self.experiment.wait(run_id)
leaderboard, status = self.experiment.leaderboard(run_id)
self.model_id = leaderboard[0]['model id']
def deploy(self):
Model(self.ctx, self.project).deploy(self.model_id, locally=True)
def predict(self):
if os.path.exists(PREDICTION_TARGET):
self.ctx.log(
"Prediction already exists."
" If you want to re-run predict, just delete prediction file: "
% PREDICTION_TARGET)
else:
Model(self.ctx, self.project).predict(PREDICTION_SOURCE,
self.model_id,
locally=True)
def cleanup(self):
self.project.delete()