ihji commented on code in PR #21809: URL: https://github.com/apache/beam/pull/21809#discussion_r912223535
########## sdks/java/extensions/python/src/main/java/org/apache/beam/sdk/extensions/python/transforms/RunInference.java: ########## @@ -0,0 +1,102 @@ +/* + * 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. + */ +package org.apache.beam.sdk.extensions.python.transforms; + +import java.util.Map; +import org.apache.beam.sdk.coders.RowCoder; +import org.apache.beam.sdk.extensions.python.PythonExternalTransform; +import org.apache.beam.sdk.schemas.Schema; +import org.apache.beam.sdk.transforms.PTransform; +import org.apache.beam.sdk.util.PythonCallableSource; +import org.apache.beam.sdk.values.PCollection; +import org.apache.beam.sdk.values.Row; +import org.apache.beam.vendor.guava.v26_0_jre.com.google.common.collect.ImmutableMap; + +/** Wrapper for invoking external Python RunInference. */ +public class RunInference extends PTransform<PCollection<?>, PCollection<Row>> { + private final String modelLoader; + private final Schema schema; + private final Map<String, Object> kwargs; + private final String expansionService; + + /** + * Instantiates a multi-language wrapper for a Python RunInference with a given model loader. + * + * @param modelLoader A Python lambda function for a model loader class object. + * @param exampleType A schema field type for the example column in output rows. + * @param inferenceType A schema field type for the inference column in output rows. + * @return A {@link RunInference} for the given model loader. + */ + public static RunInference of( + String modelLoader, Schema.FieldType exampleType, Schema.FieldType inferenceType) { + Schema schema = + Schema.of( + Schema.Field.of("example", exampleType), Schema.Field.of("inference", inferenceType)); + return new RunInference(modelLoader, schema, ImmutableMap.of(), ""); + } + + /** + * Instantiates a multi-language wrapper for a Python RunInference with a given model loader. + * + * @param modelLoader A Python lambda function for a model loader class object. + * @param schema A schema for output rows. + * @return A {@link RunInference} for the given model loader. + */ + public static RunInference of(String modelLoader, Schema schema) { + return new RunInference(modelLoader, schema, ImmutableMap.of(), ""); + } + + /** + * Sets keyword arguments for RunInference constructor. + * + * @return A {@link RunInference} with keyword arguments. + */ + public RunInference withKwarg(String key, Object arg) { + ImmutableMap.Builder<String, Object> builder = + ImmutableMap.<String, Object>builder().putAll(kwargs).put(key, arg); + return new RunInference(modelLoader, schema, builder.build(), expansionService); + } + + /** + * Sets an expansion service endpoint for RunInference. + * + * @param expansionService A URL for a Python expansion service. + * @return A {@link RunInference} for the given expansion service endpoint. + */ + public RunInference withExpansionService(String expansionService) { + return new RunInference(modelLoader, schema, kwargs, expansionService); + } + + private RunInference( + String modelLoader, Schema schema, Map<String, Object> kwargs, String expansionService) { + this.modelLoader = modelLoader; + this.schema = schema; + this.kwargs = kwargs; + this.expansionService = expansionService; + } + + @Override + public PCollection<Row> expand(PCollection<?> input) { + return input.apply( + PythonExternalTransform.<PCollection<?>, PCollection<Row>>from( + "apache_beam.ml.inference.base.RunInference.create", expansionService) + .withKwarg("model_handler_provider", PythonCallableSource.of(modelLoader)) + .withKwargs(kwargs) + .withOutputCoder(RowCoder.of(schema))); Review Comment: Yes, ideally the Python SDK should be all responsible for inferring output coders but in reality there are many instances that the type inference doesn’t work as expected. Users may want to use `withOutputCoder` method for giving a hint to the Python SDK (it’s optional and not guaranteed to be satisfied). -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
