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build: Add default value for argument 'TRITON_REPO_ORGANIZATION' from sdk Dockerfile (#7437)
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Dockerfile.sdk

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@@ -33,6 +33,7 @@ ARG BASE_IMAGE=nvcr.io/nvidia/tritonserver:24.07-py3-min
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ARG TRITON_CLIENT_REPO_SUBDIR=clientrepo
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ARG TRITON_PA_REPO_SUBDIR=perfanalyzerrepo
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ARG TRITON_REPO_ORGANIZATION=http://github.com/triton-inference-server
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ARG TRITON_COMMON_REPO_TAG=main
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ARG TRITON_CORE_REPO_TAG=main
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ARG TRITON_CLIENT_REPO_TAG=main

docs/customization_guide/build.md

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@@ -331,13 +331,13 @@ invocation builds all features and backends available on windows.
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python build.py --cmake-dir=<path/to/repo>/build --build-dir=/tmp/citritonbuild --no-container-pull --image=base,win10-py3-min --enable-logging --enable-stats --enable-tracing --enable-gpu --endpoint=grpc --endpoint=http --repo-tag=common:<container tag> --repo-tag=core:<container tag> --repo-tag=backend:<container tag> --repo-tag=thirdparty:<container tag> --backend=ensemble --backend=tensorrt:<container tag> --backend=onnxruntime:<container tag> --backend=openvino:<container tag>
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```
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If you are building on *main* branch then '<container tag>' will
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If you are building on *main* branch then `<container tag>` will
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default to "main". If you are building on a release branch then
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'<container tag>' will default to the branch name. For example, if you
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are building on the r24.07 branch, '<container tag>' will default to
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r24.07. Therefore, you typically do not need to provide '<container
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tag>' at all (nor the preceding colon). You can use a different
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'<container tag>' for a component to instead use the corresponding
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`<container tag>` will default to the branch name. For example, if you
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are building on the r24.07 branch, `<container tag>` will default to
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r24.07. Therefore, you typically do not need to provide `<container
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tag>` at all (nor the preceding colon). You can use a different
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`<container tag>` for a component to instead use the corresponding
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branch/tag in the build. For example, if you have a branch called
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"mybranch" in the
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[onnxruntime_backend](https://github.com/triton-inference-server/onnxruntime_backend)

docs/customization_guide/test.md

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@@ -48,7 +48,7 @@ $ ./gen_qa_model_repository
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$ ./gen_qa_custom_ops
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```
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This will create multiple model repositories in /tmp/<version>/qa_*
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This will create multiple model repositories in /tmp/\<version\>/qa_*
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(for example /tmp/24.07/qa_model_repository). The TensorRT models
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will be created for the GPU on the system that CUDA considers device 0
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(zero). If you have multiple GPUs on your system see the documentation
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## Build SDK Image
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Build the *tritonserver_sdk* image that contains the client
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libraries, model analyzer, and examples using the following
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commands. You must first checkout the <client branch> branch of the
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*client* repo into the clientrepo/ subdirectory. Typically you want to
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set <client branch> to be the same as your current server branch.
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libraries, model analyzer, perf analyzer and examples using the following
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commands. You must first checkout the `<client branch>` branch of the
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*client* repo into the clientrepo/ subdirectory and the `<perf analyzer branch>`
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branch of the *perf_analyzer* repo into the perfanalyzerrepo/ subdirectory
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respectively. Typically you want to set both `<client branch>` and `<perf analyzer branch>`
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to be the same as your current server branch.
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```
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$ cd <server repo root>
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$ git clone --single-branch --depth=1 -b <client branch> https://github.com/triton-inference-server/client.git clientrepo
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$ git clone --single-branch --depth=1 -b <perf analyzer branch> https://github.com/triton-inference-server/perf_analyzer.git perfanalyzerrepo
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$ docker build -t tritonserver_sdk -f Dockerfile.sdk .
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```
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