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https://github.com/saymrwulf/onnxruntime.git
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dbc7a195b1
1. Enable xnnpack test 2. Change TSA database name from onnxruntime_master to onnxruntime_main. This is a leftover of renaming the "master" branch to "main" 3. Add two static analysis jobs for WinML and DML 4. Rename the machine pool "aiinfra-dml-winbuild" to "onnxruntime-Win2019-GPU-dml-A10", so that the internal and public ADO instances use the same machine pool name. 5. Move Windows GPU CI build pipeline from "onnxruntime-Win2022-GPU-T4" to "onnxruntime-Win2022-GPU-A10" machine pool, because we do not have enough T4 GPUs.
11 lines
639 B
Batchfile
11 lines
639 B
Batchfile
REM Copyright (c) Microsoft Corporation. All rights reserved.
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REM Licensed under the MIT License.
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if exist PATH=%AGENT_TEMPDIRECTORY%\v11.8\ {
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set PATH=%AGENT_TEMPDIRECTORY%\v11.8\bin;%AGENT_TEMPDIRECTORY%\v11.8\extras\CUPTI\lib64;%PATH%
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} else {
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set PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin;C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\extras\CUPTI\lib64;%PATH%
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}
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set PATH=C:\local\TensorRT-8.6.0.12.Windows10.x86_64.cuda-11.8\lib;C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\MSBuild\Current\Bin;%PATH%
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set GRADLE_OPTS=-Dorg.gradle.daemon=false
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set CUDA_MODULE_LOADING=LAZY
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