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https://issues.apache.org/jira/browse/BEAM-9421?focusedWorklogId=402949&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-402949
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ASF GitHub Bot logged work on BEAM-9421:
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Author: ASF GitHub Bot
Created on: 13/Mar/20 15:40
Start Date: 13/Mar/20 15:40
Worklog Time Spent: 10m
Work Description: kamilwu commented on pull request #11075: [BEAM-9421]
Website section that describes getting predictions using AI Platform Prediciton
URL: https://github.com/apache/beam/pull/11075#discussion_r392306737
##########
File path: website/src/documentation/patterns/ai-platform.md
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@@ -0,0 +1,87 @@
+---
+layout: section
+title: "AI Platform integration patterns"
+section_menu: section-menu/documentation.html
+permalink: /documentation/patterns/ai-platform/
+---
+<!--
+Licensed 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.
+-->
+
+# AI Platform integration patterns
+
+This page describes common patterns in pipelines with Google AI Platform
transforms.
+
+<nav class="language-switcher">
+ <strong>Adapt for:</strong>
+ <ul>
+ <li data-type="language-java">Java SDK</li>
+ <li data-type="language-py" class="active">Python SDK</li>
+ </ul>
+</nav>
+
+## Getting predictions
+
+This section shows how to use your cloud-hosted machine learning model to make
predictions about new data using Google Cloud AI Platform Prediction within
Beam's pipeline.
+
+We are going to use [tfx_bsl](https://github.com/tensorflow/tfx-bsl) library
which provides `RunInference` Beam's PTransform. `RunInference` is a PTransform
able to perform two types of inference. In this section we are going to
consider one of them that uses a service endpoint. When using a service
endpoint, the transform takes a PCollection of type `tf.train.Example` and, for
each element, sends a request to Google Cloud AI Platform Prediction service.
The transform produces a PCollection of type `PredictLog` which contains
predictions.
+
+Before we get started, we have to deploy a machine learning model to the
cloud. The cloud service manages the infrastructure needed to handle prediction
requests in both efficient and scalable way. Only Tensorflow models are
supported. For more information, see [Exporting a SavedModel for
prediction](https://cloud.google.com/ai-platform/prediction/docs/exporting-savedmodel-for-prediction).
+
+Let's show an example of a pipeline that reads input instances from the file,
converts JSON objects to `tf.train.Example` objects and sends data to the
service. The content of a file can look like this:
+
+```
+{"input": "the quick brown"}
+{"input": "la bruja le"}
+```
+
+Here is the code:
+
+{:.language-java}
+```java
+// Getting predictions is not available for Java.
Review comment:
Done.
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Issue Time Tracking
-------------------
Worklog Id: (was: 402949)
Time Spent: 1.5h (was: 1h 20m)
> AI Platform pipeline patterns
> -----------------------------
>
> Key: BEAM-9421
> URL: https://issues.apache.org/jira/browse/BEAM-9421
> Project: Beam
> Issue Type: Sub-task
> Components: website
> Reporter: Kamil Wasilewski
> Assignee: Kamil Wasilewski
> Priority: Major
> Labels: pipeline-patterns
> Time Spent: 1.5h
> Remaining Estimate: 0h
>
> New pipeline patterns should be contributed to the Beam's website in order to
> demonstrate how newly implemented Google Cloud AI PTransforms can be used in
> pipelines.
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