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Update SDK build instructions (triton-inference-server#3042)
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deadeyegoodwin authored Jun 24, 2021
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<!--
# Copyright (c) 2018-2021, NVIDIA CORPORATION. All rights reserved.
# Copyright 2018-2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
Expand Down Expand Up @@ -49,7 +49,7 @@ $ ./gen_qa_custom_ops
```

This will create multiple model repositories in /tmp/<version>/qa_*
(for example /tmp/19.08/qa_model_repository). The TensorRT models
(for example /tmp/21.05/qa_model_repository). The TensorRT models
will be created for the GPU on the system that CUDA considers device 0
(zero). If you have multiple GPUs on your system see the documentation
in the scripts for how to target a specific GPU.
Expand All @@ -60,11 +60,16 @@ Next you need to build a QA version of the Triton Docker image. This
image will contain Triton, the QA tests, and all the dependencies
needed to run the QA tests. First do a [Docker image
build](build.md#building-triton-with-docker) to produce the
*tritonserver_build* and *tritonserver* images. Then build the
*tritonserver_sdk* image that contains the client libraries,
model analyzer, and examples.
*tritonserver_build* and *tritonserver* images.

Then build the *tritonserver_sdk* image that contains the client
libraries, model analyzer, and examples using the following
commands. You must first checkout the <client branch> branch of the
*client* repo into the clientrepo/ subdirectory. Typically you want to
set <client branch> to be the same as your current server branch.

```
$ git clone --single-branch --depth=1 -b <client branch> https://github.com/triton-inference-server/client.git clientrepo
$ docker build -t tritonserver_sdk -f Dockerfile.sdk .
```

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