def get_job_metrics(self, request, context):
with self._app.app_context():
job = self._check_metrics_public(request, context)
metrics = JobMetricsBuilder(job).plot_metrics()
return service_pb2.GetJobMetricsResponse(
status=common_pb2.Status(code=common_pb2.STATUS_SUCCESS),
metrics=json.dumps(metrics))
def get(self, job_id):
job = _get_job(job_id)
metrics = JobMetricsBuilder(job).plot_metrics()
# Metrics is a list of dict. Each dict can be rendered by frontend with
# mpld3.draw_figure('figure1', json)
return {'data': metrics}
def get(self, job_id):
job = _get_job(job_id)
try:
metrics = JobMetricsBuilder(job).plot_metrics()
# Metrics is a list of dict. Each dict can be rendered by frontend
# with mpld3.draw_figure('figure1', json)
return {'data': metrics}
except Exception as e: # pylint: disable=broad-except
abort(400, message=repr(e))
def get(self, job_id):
job = Job.query.filter_by(id=job_id).first()
if job is None:
raise NotFoundException()
metrics = JobMetricsBuilder(job).plot_metrics()
# Metrics is a list of dict. Each dict can be rendered by frontend with
# mpld3.draw_figure('figure1', json)
return {'data': metrics}
def get_job_metrics(self, request, context):
with self._app.app_context():
project, party = self.check_auth_info(request.auth_info, context)
job = Job.query.filter_by(name=request.job_name,
project_id=project.id).first()
assert job is not None, f'Job {request.job_name} not found'
workflow = job.workflow
if not workflow.metric_is_public:
raise UnauthorizedException('Metric is private!')
metrics = JobMetricsBuilder(job).plot_metrics()
return service_pb2.GetJobMetricsResponse(
status=common_pb2.Status(code=common_pb2.STATUS_SUCCESS),
metrics=json.dumps(metrics))
def on_job_update(self, job):
model = Model.query.filter_by(job_name=job.name).one()
# https://code.byted.org/data/fedlearner_web_console_v2/merge_requests/101
state = job.get_result_state()
if model.state != ModelState.RUNNING and state == 'RUNNING':
model.version += 1
model.state = self.job_state_map[state]
model.commit()
if model.state in [
ModelState.FINISHED, ModelState.SUCCEEDED, ModelState.FAILED
]:
try:
metrics = JobMetricsBuilder(job).plot_metrics()
model.metrics = json.dumps(metrics)
model.commit()
except Exception as e:
logging.warning('Error building metrics: %s', repr(e))
def query(self, model_id, detail_level=0):
"""
Query a model
Args:
model_id: model id
detail_level: 0, return basic info; 1, query the es
Returns:
return model json
"""
model = Model.query.filter_by(id=model_id).one()
model_json = model.to_dict()
model_json['detail_level'] = detail_level
if detail_level == 0:
return model_json
try:
job = Job.query.filter_by(name=model.job_name).one()
metrics = JobMetricsBuilder(job).plot_metrics()
model_json['metrics'] = json.dumps(metrics)
except Exception as e:
logging.warning('Error building metrics: %s', repr(e))
return model_json
def get_job_metrics(self, request, context):
with self._app.app_context():
project, party = self.check_auth_info(request.auth_info, context)
workflow = Workflow.query.filter_by(
name=request.workflow_name).first()
assert workflow is not None, \
f'Workflow {request.workflow_name} not found'
if not workflow.metric_is_public:
raise UnauthorizedException('Metric is private!')
job = None
for i in workflow.get_jobs():
if i.get_config().name == request.job_name:
job = i
break
assert job is not None, f'Job {request.job_name} not found'
metrics = JobMetricsBuilder(job).plot_metrics()
return service_pb2.GetJobMetricsResponse(
status=common_pb2.Status(code=common_pb2.STATUS_SUCCESS),
metrics=json.dumps(metrics))
def test_nn_metrics(self):
job = Job(name='automl-2782410011',
job_type=JobType.NN_MODEL_TRANINING)
print(JobMetricsBuilder(job).plot_metrics())
def test_data_join_metrics(self):
job = Job(name='multi-indices-test27', job_type=JobType.DATA_JOIN)
import json
print(json.dumps(JobMetricsBuilder(job).plot_metrics()))
def plot_metrics(self, model, job=None):
try:
return JobMetricsBuilder(job or model.job).plot_metrics()
except Exception as e:
return repr(e)