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https://issues.apache.org/jira/browse/BEAM-13983?focusedWorklogId=761021&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-761021
]
ASF GitHub Bot logged work on BEAM-13983:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 22/Apr/22 18:54
Start Date: 22/Apr/22 18:54
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on code in PR #17368:
URL: https://github.com/apache/beam/pull/17368#discussion_r856490682
##########
sdks/python/apache_beam/ml/inference/sklearn_loader.py:
##########
@@ -0,0 +1,78 @@
+#
+# 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.
+#
+
+import enum
+import pickle
+import sys
+from typing import Any
+from typing import Iterable
+from typing import List
+
+import numpy
+
+from apache_beam.io.filesystems import FileSystems
+from apache_beam.ml.inference.api import PredictionResult
+from apache_beam.ml.inference.base import InferenceRunner
+from apache_beam.ml.inference.base import ModelLoader
+
+try:
+ import joblib
+except ImportError:
+ # joblib is an optional dependency.
+ pass
+
+
+class ModelFileType(enum.Enum):
+ PICKLE = 1
+ JOBLIB = 2
+
+
+class SklearnInferenceRunner(InferenceRunner):
+ def run_inference(self, batch: List[numpy.array],
+ model: Any) -> Iterable[numpy.array]:
+ # vectorize data for better performance
+ vectorized_batch = numpy.stack(batch, axis=0)
+ predictions = model.predict(vectorized_batch)
+ return [PredictionResult(x, y) for x, y in zip(batch, predictions)]
+
+ def get_num_bytes(self, batch: List[numpy.array]) -> int:
+ """Returns the number of bytes of data for a batch."""
+ return sum(sys.getsizeof(element) for element in batch)
+
+
+class SklearnModelLoader(ModelLoader):
+ def __init__(
+ self,
+ model_file_type: ModelFileType = ModelFileType.PICKLE,
+ model_uri: str = ''):
+ self._model_file_type = model_file_type
+ self._model_uri = model_uri
+ self._inference_runner = SklearnInferenceRunner()
+
+ def load_model(self):
+ """Loads and initializes a model for processing."""
+ file = FileSystems.open(self._model_uri, 'rb')
+ if self._model_file_type == ModelFileType.PICKLE:
+ return pickle.load(file)
+ elif self._model_file_type == ModelFileType.JOBLIB:
+ if not joblib:
+ raise ImportError('Joblib not available in SklearnModelLoader.')
Review Comment:
Note this will be an execution time error causing workers to crash, which
isn't a great experience. You might consider pointing this to some
documentation about setting up dependencies.
##########
sdks/python/setup.py:
##########
@@ -169,6 +170,7 @@ def get_version():
'pytest>=4.4.0,<5.0',
'pytest-xdist>=1.29.0,<2',
'pytest-timeout>=1.3.3,<2',
+ 'scikit-learn>=0.24.2',
Review Comment:
It would be good to get an answer on the above (and similarly for joblib)
##########
sdks/python/apache_beam/ml/inference/sklearn_loader.py:
##########
@@ -0,0 +1,78 @@
+#
+# 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.
+#
+
+import enum
+import pickle
+import sys
+from typing import Any
+from typing import Iterable
+from typing import List
+
+import numpy
+
+from apache_beam.io.filesystems import FileSystems
+from apache_beam.ml.inference.api import PredictionResult
+from apache_beam.ml.inference.base import InferenceRunner
+from apache_beam.ml.inference.base import ModelLoader
+
+try:
+ import joblib
+except ImportError:
+ # joblib is an optional dependency.
+ pass
+
+
+class ModelFileType(enum.Enum):
+ PICKLE = 1
+ JOBLIB = 2
+
+
+class SklearnInferenceRunner(InferenceRunner):
+ def run_inference(self, batch: List[numpy.array],
+ model: Any) -> Iterable[numpy.array]:
+ # vectorize data for better performance
+ vectorized_batch = numpy.stack(batch, axis=0)
+ predictions = model.predict(vectorized_batch)
+ return [PredictionResult(x, y) for x, y in zip(batch, predictions)]
+
+ def get_num_bytes(self, batch: List[numpy.array]) -> int:
+ """Returns the number of bytes of data for a batch."""
+ return sum(sys.getsizeof(element) for element in batch)
+
+
+class SklearnModelLoader(ModelLoader):
+ def __init__(
+ self,
+ model_file_type: ModelFileType = ModelFileType.PICKLE,
+ model_uri: str = ''):
+ self._model_file_type = model_file_type
+ self._model_uri = model_uri
+ self._inference_runner = SklearnInferenceRunner()
+
+ def load_model(self):
+ """Loads and initializes a model for processing."""
+ file = FileSystems.open(self._model_uri, 'rb')
+ if self._model_file_type == ModelFileType.PICKLE:
+ return pickle.load(file)
+ elif self._model_file_type == ModelFileType.JOBLIB:
+ if not joblib:
+ raise ImportError('Joblib not available in SklearnModelLoader.')
+ return joblib.load(file)
+ raise TypeError('Unsupported serialization type.')
Review Comment:
nit: I might make this an assertion error since it's a state we shouldn't
get to given ModelFileType is an enum.
Issue Time Tracking
-------------------
Worklog Id: (was: 761021)
Time Spent: 4h 40m (was: 4.5h)
> Implement RunInference for Scikit-learn
> ---------------------------------------
>
> Key: BEAM-13983
> URL: https://issues.apache.org/jira/browse/BEAM-13983
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-py-core
> Reporter: Andy Ye
> Assignee: Ryan Thompson
> Priority: P2
> Labels: run-inference
> Time Spent: 4h 40m
> Remaining Estimate: 0h
>
> Implement RunInference for Scikit-learn as described in the design doc
> [https://s.apache.org/inference-sklearn-pytorch]
> There will be a sklearn_impl.py file that contains SklearnModelLoader and
> SlkearnInferenceRunner classes.
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