[GitHub] [beam] AnandInguva commented on a diff in pull request #24965: XGBoost modelhandler implementation

["AnandInguva (via GitHub)" <gi...@apache.org>]

AnandInguva commented on code in PR #24965:
URL: https://github.com/apache/beam/pull/24965#discussion_r1096930767


##########
sdks/python/apache_beam/ml/inference/xgboost_inference.py:
##########
@@ -0,0 +1,370 @@
+#
+# 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 sys
+from abc import ABC
+from typing import Any
+from typing import Callable
+from typing import Dict
+from typing import Iterable
+from typing import Optional
+from typing import Sequence
+from typing import Union
+
+import datatable
+import numpy
+import pandas
+import scipy
+import xgboost
+
+from apache_beam.io.filesystems import FileSystems
+from apache_beam.ml.inference.base import ExampleT
+from apache_beam.ml.inference.base import ModelHandler
+from apache_beam.ml.inference.base import ModelT
+from apache_beam.ml.inference.base import PredictionResult
+from apache_beam.ml.inference.base import PredictionT
+
+__all__ = [
+    'XGBoostModelHandler',
+    'XGBoostModelHandlerNumpy',
+    'XGBoostModelHandlerPandas',
+    'XGBoostModelHandlerSciPy',
+    'XGBoostModelHandlerDatatable'
+]
+
+XGBoostInferenceFn = Callable[[
+    Sequence[object],
+    Union[xgboost.Booster, xgboost.XGBModel],
+    Optional[Dict[str, Any]]
+],
+                              Iterable[PredictionResult]]
+
+
+def default_xgboost_inference_fn(
+    batch: Sequence[object],
+    model: Union[xgboost.Booster, xgboost.XGBModel],
+    inference_args: Optional[Dict[str, Any]] = None):
+  inference_args = {} if not inference_args else inference_args
+
+  if type(model) == xgboost.Booster:
+    batch = (xgboost.DMatrix(array) for array in batch)
+  predictions = [model.predict(el, **inference_args) for el in batch]
+
+  return [PredictionResult(x, y) for x, y in zip(batch, predictions)]
+
+
+class XGBoostModelHandler(ModelHandler[ExampleT, PredictionT, ModelT], ABC):
+
+  def __init__(
+      self,
+      model_class: Union[Callable[..., xgboost.Booster],
+                         Callable[..., xgboost.XGBModel]],
+      model_state: str,
+      inference_fn: XGBoostInferenceFn = default_xgboost_inference_fn):
+    """Implementation of the ModelHandler interface for XGBoost.
+
+    Example Usage::
+
+        pcoll | RunInference(
+                    XGBoostModelHandler(
+                        model_class="XGBoost Model Class",
+                        model_state="my_model_state.json")))
+
+    See https://xgboost.readthedocs.io/en/stable/tutorials/saving_model.html
+    for details
+
+    Args:
+    model_class: class of the XGBoost model that defines the model
+      structure.
+    model_state: path to a json file that contains the model's
+      configuration.
+    inference_fn: the inference function to use during RunInference.
+      default=default_xgboost_inference_fn
+
+    **Supported Versions:** RunInference APIs in Apache Beam have been tested
+    with PyTorch 1.6.0 and 1.7.0

Review Comment:
   ```suggestion
       with XGBoost 1.6.0 and 1.7.0
   ```
   



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