#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from typing import Any
from typing import Dict
from typing import Optional
import apache_beam as beam
from apache_beam.ml.anomaly.base import AnomalyDetector
from apache_beam.ml.anomaly.specifiable import specifiable
from apache_beam.ml.inference.base import KeyedModelHandler
[docs]
@specifiable
class OfflineDetector(AnomalyDetector):
"""A offline anomaly detector that uses a provided model handler for scoring.
Args:
keyed_model_handler: The model handler to use for inference.
Requires a `KeyModelHandler[Any, Row, float, Any]` instance.
run_inference_args: Optional arguments to pass to RunInference
**kwargs: Additional keyword arguments to pass to the base
AnomalyDetector class.
"""
def __init__(
self,
keyed_model_handler: KeyedModelHandler[Any, beam.Row, float, Any],
run_inference_args: Optional[Dict[str, Any]] = None,
**kwargs):
super().__init__(**kwargs)
# TODO: validate the model handler type
self._keyed_model_handler = keyed_model_handler
self._run_inference_args = run_inference_args or {}
# always override model_identifier with model_id from the detector
self._run_inference_args["model_identifier"] = self._model_id
[docs]
def learn_one(self, x: beam.Row) -> None:
"""Not implemented since OfflineDetector invokes RunInference directly."""
raise NotImplementedError
[docs]
def score_one(self, x: beam.Row) -> Optional[float]:
"""Not implemented since OfflineDetector invokes RunInference directly."""
raise NotImplementedError