[GitHub] [beam] yeandy commented on a change in pull request #16917: [BEAM-13972] Add RunInference interface

[GitBox <gi...@apache.org>]

yeandy commented on a change in pull request #16917:
URL: https://github.com/apache/beam/pull/16917#discussion_r817201017



##########
File path: sdks/python/apache_beam/ml/inference/api.py
##########
@@ -0,0 +1,84 @@
+#
+# 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 dataclasses import dataclass
+import apache_beam as beam
+from typing import Tuple, TypeVar, Union
+# TODO: implement RunInferenceImpl
+# from apache_beam.ml.inference.base import RunInferenceImpl
+
+
+@dataclass
+class BaseModelSpec:
+  model_url: str
+
+
+@dataclass
+class PyTorchModel(BaseModelSpec):
+  device: str
+
+  def __post_init__(self):
+    self.device = self.device.upper()
+
+
+@dataclass
+class SklearnModel(BaseModelSpec):
+  serialization_type: str
+
+  def __post_init__(self):
+    self.serialization_type = self.serialization_type.upper()
+
+
+_K = TypeVar('_K')
+_INPUT_TYPE = TypeVar('_INPUT_TYPE')
+_OUTPUT_TYPE = TypeVar('_OUTPUT_TYPE')
+
+
+@dataclass
+class PredictionResult:
+  key: _K
+  example: _INPUT_TYPE
+  inference: _OUTPUT_TYPE
+
+
+@beam.ptransform_fn
+@beam.typehints.with_input_types(Union[_INPUT_TYPE, Tuple[_K, _INPUT_TYPE]])
+@beam.typehints.with_output_types(PredictionResult)

Review comment:
       How should we deal with typing? TFX [explicitly](https://github.com/tensorflow/tfx-bsl/blob/v1.6.0/tfx_bsl/public/beam/run_inference.py#L34) defines output as `Union[_OUTPUT_TYPE, Tuple[_K, _OUTPUT_TYPE]]`




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