def get_mlops_stat(self, model_id):
data = self._to_dict()
mlops_stat = MLOpsStat(name=self._name,
stat_type=InfoType_pb2.General,
graph_type=StatGraphType.BARGRAPH,
mode=StatsMode.Instant,
data=data,
model_id=model_id)
return mlops_stat
def get_mlops_stat(self, model_id):
if self._data is None:
raise MLOpsException("There is no data in html object")
mlops_stat = MLOpsStat(name=self._name,
stat_type=InfoType_pb2.General,
graph_type=StatGraphType.HTML,
mode=StatsMode.Instant,
json_data_dump=self._data,
model_id=model_id)
return mlops_stat
def get_mlops_stat(self, model_id):
graph_type = StatGraphType.LINEGRAPH
formatted_value = ValueFormatter(self._name, self._value, graph_type).value()
mlops_stat = MLOpsStat(name=self._name,
stat_type=InfoType_pb2.KPI,
graph_type=graph_type,
mode=StatsMode.TimeSeries,
data=formatted_value,
timestamp_ns=self._timestamp_ns,
model_id=model_id)
return mlops_stat
def get_mlops_stat(self, model_id):
if self._data is None:
raise MLOpsException("There is no data in opaque stat")
data = self._to_dict()
mlops_stat = MLOpsStat(name=self._name,
stat_type=InfoType_pb2.General,
graph_type=StatGraphType.OPAQUE,
mode=StatsMode.Instant,
data=data,
model_id=model_id)
return mlops_stat
def get_mlops_stat(self, model_id):
if len(self._feature_value) == 0:
raise MLOpsException("There is no data in histogram graph")
data = self._to_dict()
mlops_stat = MLOpsStat(name=self._name,
stat_table=self._name,
stat_type=self._stat_type,
graph_type=StatGraphType.BARGRAPH,
mode=StatsMode.Instant,
data=data,
model_id=model_id)
return mlops_stat
def get_mlops_stat(self, model_id):
if self._x_series is None:
raise MLOpsException("No x_series was provided")
if len(self._y_series) == 0:
raise MLOpsException("At leat one y_series should be provided")
tbl_data = self._to_dict()
mlops_stat = MLOpsStat(name=self._name,
stat_type=InfoType_pb2.General,
graph_type=StatGraphType.GENERAL_GRAPH,
mode=StatsMode.Instant,
data=tbl_data,
model_id=model_id)
return mlops_stat
def get_mlops_stat(self, model_id):
if len(self._tbl_rows) == 0:
raise MLOpsException("No rows data found in table object")
tbl_data = self._to_semi_json(escape=False)
semi_json = self._to_semi_json()
mlops_stat = MLOpsStat(name=self._name,
stat_type=InfoType_pb2.General,
graph_type=StatGraphType.MATRIX,
mode=StatsMode.Instant,
data=tbl_data,
string_data=semi_json,
json_data_dump=tbl_data,
model_id=model_id)
return mlops_stat
def get_mlops_stat(self, model_id):
if len(self._data) == 0:
raise MLOpsException("There is no data in heat graph")
if len(self._feature_names) == 0:
raise MLOpsException("No columns names were provided")
if len(self._data) != len(self._feature_names):
raise MLOpsException(
"Number of data point does not match number of columns")
data = self._to_dict()
mlops_stat = MLOpsStat(name=self._name,
stat_table=self._name,
stat_type=InfoType_pb2.General,
graph_type=StatGraphType.HEATMAP,
mode=StatsMode.TimeSeries,
data=data,
model_id=model_id)
return mlops_stat
def get_mlops_stat(self, model_id):
if len(self._data) == 0:
raise MLOpsException("There is no data in histogram score")
if len(self._feature_names) == 0:
raise MLOpsException("No columns names were provided")
if len(self._data) != len(self._feature_names):
raise MLOpsException(
"Number of data point does not match number of columns")
data = self._to_dict()
mlops_stat = MLOpsStat(name=self._name,
stat_table=self._name,
stat_type=InfoType_pb2.HealthCompare,
graph_type=StatGraphType.MULTILINEGRAPH,
mode=StatsMode.TimeSeries,
data=data,
model_id=model_id)
return mlops_stat
def get_mlops_stat(self, model_id):
if len(self._data) == 0:
raise MLOpsException("There is no data in multi line graph")
if len(self._label_list) == 0:
raise MLOpsException(
"MultiLineGraph labels number does not match number of data points"
)
if len(self._data) != len(self._label_list):
raise MLOpsException(
"number of data point does not match number of labels")
multiline_data = self._to_dict()
mlops_stat = MLOpsStat(name=self._name,
stat_type=InfoType_pb2.General,
graph_type=StatGraphType.MULTILINEGRAPH,
mode=StatsMode.TimeSeries,
data=multiline_data,
model_id=model_id)
return mlops_stat