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https://issues.apache.org/jira/browse/BEAM-9421?focusedWorklogId=434907&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-434907
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ASF GitHub Bot logged work on BEAM-9421:
----------------------------------------
Author: ASF GitHub Bot
Created on: 19/May/20 11:26
Start Date: 19/May/20 11:26
Worklog Time Spent: 10m
Work Description: kamilwu commented on a change in pull request #11075:
URL: https://github.com/apache/beam/pull/11075#discussion_r427227456
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File path: website/www/site/content/en/documentation/patterns/ai-platform.md
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@@ -0,0 +1,79 @@
+---
+title: "AI Platform integration patterns"
+---
+<!--
+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 Cloud AI Platform
transforms.
+
+{{< language-switcher java py >}}
+
+## Getting predictions
+
+This section shows how to use [Google Cloud AI Platform
Prediction](https://cloud.google.com/ai-platform/prediction/docs/overview) to
make predictions about new data from a cloud-hosted machine learning model.
+
+[tfx_bsl](https://github.com/tensorflow/tfx-bsl) is a library with a Beam
PTransform called `RunInference`. `RunInference` is able to perform an
inference that can use an external service endpoint for receiving data. When
using a service endpoint, the transform takes a PCollection of type
`tf.train.Example` and, for every batch of elements, sends a request to AI
Platform Prediction. The size of a batch may vary. For more details on how Beam
finds the best batch size, refer to a docstring for
[BatchElements](https://beam.apache.org/releases/pydoc/current/apache_beam.transforms.util.html?highlight=batchelements#apache_beam.transforms.util.BatchElements).
+
+ The transform produces a PCollection of type `PredictionLog`, which contains
predictions.
+
+Before getting started, deploy a TensorFlow model to AI Platform Prediction.
The cloud service manages the infrastructure needed to handle prediction
requests in both efficient and scalable way. Do note that only TensorFlow
models are supported by the transform. For more information, see [Exporting a
SavedModel for
prediction](https://cloud.google.com/ai-platform/prediction/docs/exporting-savedmodel-for-prediction).
Review comment:
IIRC yes, it does not limit to tensorflow model, as long as prediction
input is valid (for instance, binary data is accepted only by tensorflow model)
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Issue Time Tracking
-------------------
Worklog Id: (was: 434907)
Time Spent: 11h 20m (was: 11h 10m)
> 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: P2
> Labels: pipeline-patterns
> Time Spent: 11h 20m
> 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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