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‎open/MLCommons/measurements/default-mlcommons_cpp-cpu-onnxruntime-default_config/README.md

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| Model | Scenario | Accuracy | Throughput | Latency (in ms) |
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|-----------|------------|------------|--------------|-------------------|
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| retinanet | offline | 49.593 | 0.419 | - |
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| retinanet | offline | 49.593 | 0.421 | - |

‎open/MLCommons/measurements/default-mlcommons_cpp-cpu-onnxruntime-default_config/retinanet/offline/README.md

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@@ -16,16 +16,16 @@ pip install -U mlcflow
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mlc rm cache -f
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mlc pull repo anandhu-eng@mlperf-automations --checkout=8bd61bc374739cf0c1f706024722559e784900eb
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mlc pull repo GATEOverflow@mlperf-automations --checkout=1ae202ac0f0fca0cb1a976c850cb69aeba0733f2
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```
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*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf,
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you should simply reload anandhu-eng@mlperf-automations without checkout and clean MLC cache as follows:*
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you should simply reload GATEOverflow@mlperf-automations without checkout and clean MLC cache as follows:*
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```bash
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mlc rm repo anandhu-eng@mlperf-automations
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mlc pull repo anandhu-eng@mlperf-automations
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mlc rm repo GATEOverflow@mlperf-automations
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mlc pull repo GATEOverflow@mlperf-automations
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mlc rm cache -f
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```
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`mAP`: `49.593`, Required accuracy for closed division `>= 37.1745`
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### Performance Results
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`Samples per second`: `0.419418`
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`Samples per second`: `0.420907`

‎open/MLCommons/measurements/default-mlcommons_cpp-cpu-onnxruntime-default_config/retinanet/offline/accuracy_console.out

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User Conf path: /home/runner/MLC/repos/anandhu-eng@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5ef036677a3b4cf5b74fe1c2204e14d7.conf
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Dataset Preprocessed path: /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-openimages_84cef78e
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Dataset List filepath: /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-openimages_84cef78e/annotations/openimages-mlperf.json
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User Conf path: /home/runner/MLC/repos/GATEOverflow@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/c6da6c9e2cb646839fd0b77e559b80d1.conf
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Dataset Preprocessed path: /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-openimages_dea2dee8
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Dataset List filepath: /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-openimages_dea2dee8/annotations/openimages-mlperf.json
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Scenario: Offline
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Mode: AccuracyOnly
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Batch size: 1

‎open/MLCommons/measurements/default-mlcommons_cpp-cpu-onnxruntime-default_config/retinanet/offline/cpu_info.json

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"MLC_HOST_CPU_L2_CACHE_SIZE": "1 MiB (2 instances)",
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"MLC_HOST_CPU_L3_CACHE_SIZE": "32 MiB (1 instance)",
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"MLC_HOST_CPU_NUMA_NODES": "1",
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"MLC_HOST_CPU_START_CORES": "0",
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"MLC_HOST_CPU_TOTAL_LOGICAL_CORES": "4",
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"MLC_HOST_CPU_TOTAL_PHYSICAL_CORES": "2",
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"MLC_HOST_CPU_PHYSICAL_CORES_LIST": "0-1",

‎open/MLCommons/measurements/default-mlcommons_cpp-cpu-onnxruntime-default_config/retinanet/offline/mlc-deps.mmd

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app-mlperf-inference,d775cac873ee4231_(_cpp,_retinanet,_onnxruntime,_cpu,_test,_r5.1-dev_default,_offline_) --> detect,os
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app-mlperf-inference,d775cac873ee4231_(_cpp,_retinanet,_onnxruntime,_cpu,_test,_r5.1-dev_default,_offline_) --> get,sys-utils-cm
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app-mlperf-inference,d775cac873ee4231_(_cpp,_retinanet,_onnxruntime,_cpu,_test,_r5.1-dev_default,_offline_) --> get,python
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app-mlperf-inference,d775cac873ee4231_(_cpp,_retinanet,_onnxruntime,_cpu,_test,_r5.1-dev_default,_offline_) --> get,mlcommons,inference,src
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get-mlperf-inference-utils,e341e5f86d8342e5 --> get,mlperf,inference,src
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get-mlperf-inference-src,4b57186581024797_(_branch.master_) --> detect,os
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get-mlperf-inference-src,4b57186581024797_(_branch.master_) --> get,python3
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get-mlperf-inference-src,4b57186581024797_(_branch.master_) --> get,git,repo,_branch.master,_repo.https://github.com/mlcommons/inference
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app-mlperf-inference,d775cac873ee4231_(_cpp,_retinanet,_onnxruntime,_cpu,_test,_r5.1-dev_default,_offline_) --> get,mlcommons,inference,src,_branch.master
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get-mlperf-inference-utils,e341e5f86d8342e5 --> get,mlperf,inference,src,_branch.master
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app-mlperf-inference,d775cac873ee4231_(_cpp,_retinanet,_onnxruntime,_cpu,_test,_r5.1-dev_default,_offline_) --> get,mlperf,inference,utils
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app-mlperf-inference-mlcommons-cpp,bf62405e6c7a44bf_(_offline,_retinanet,_onnxruntime,_cpu_) --> detect,os
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detect-cpu,586c8a43320142f7 --> detect,os
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get-generic-python-lib,94b62a682bc44791_(_package.setuptools_) --> get,generic-python-lib,_pip
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get-mlperf-inference-loadgen,64c3d98d0ba04950_(_wg-inference_) --> get,generic-python-lib,_package.setuptools
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app-mlperf-inference-mlcommons-cpp,bf62405e6c7a44bf_(_offline,_retinanet,_onnxruntime,_cpu_) --> get,loadgen,_wg-inference
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app-mlperf-inference-mlcommons-cpp,bf62405e6c7a44bf_(_offline,_retinanet,_onnxruntime,_cpu_) --> get,mlcommons,inference,src
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app-mlperf-inference-mlcommons-cpp,bf62405e6c7a44bf_(_offline,_retinanet,_onnxruntime,_cpu_) --> get,mlcommons,inference,src,_branch.master
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app-mlperf-inference-mlcommons-cpp,bf62405e6c7a44bf_(_offline,_retinanet,_onnxruntime,_cpu_) --> get,lib,onnxruntime,lang-cpp,_cpu
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app-mlperf-inference-mlcommons-cpp,bf62405e6c7a44bf_(_offline,_retinanet,_onnxruntime,_cpu_) --> get,dataset,preprocessed,openimages,_validation,_NCHW,_50
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app-mlperf-inference-mlcommons-cpp,bf62405e6c7a44bf_(_offline,_retinanet,_onnxruntime,_cpu_) --> get,ml-model,retinanet,_onnx,_fp32
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generate-mlperf-inference-user-conf,3af4475745964b93_(_wg-inference_) --> get,python
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get-mlperf-inference-sut-configs,c2fbf72009e2445b --> get,cache,dir,_name.mlperf-inference-sut-configs
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generate-mlperf-inference-user-conf,3af4475745964b93_(_wg-inference_) --> get,sut,configs
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generate-mlperf-inference-user-conf,3af4475745964b93_(_wg-inference_) --> get,mlcommons,inference,src
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generate-mlperf-inference-user-conf,3af4475745964b93_(_wg-inference_) --> get,mlcommons,inference,src,_branch.master
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app-mlperf-inference-mlcommons-cpp,bf62405e6c7a44bf_(_offline,_retinanet,_onnxruntime,_cpu_) --> generate,user-conf,mlperf,inference,_wg-inference
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detect-cpu,586c8a43320142f7 --> detect,os
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compile-program,c05042ba005a4bfa --> detect,cpu

‎open/MLCommons/measurements/default-mlcommons_cpp-cpu-onnxruntime-default_config/retinanet/offline/mlc-deps.png

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‎open/MLCommons/measurements/default-mlcommons_cpp-cpu-onnxruntime-default_config/retinanet/offline/mlc-version-info.json

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}
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},
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{
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"get,mlcommons,inference,src": {
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"detect,os": {
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"script_uid": "863735b7db8c44fc",
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"script_alias": "detect-os",
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"script_tags": "detect-os,detect,os,info",
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"script_variations": "",
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"version": "",
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"parent": "get-mlperf-inference-src,4b57186581024797 ( branch.master )"
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}
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{
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"get,python3": {
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"script_uid": "d0b5dd74373f4a62",
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"script_alias": "get-python3",
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"script_tags": "get,python,python3,get-python,get-python3",
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"script_variations": "",
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"version": "3.10.8",
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"parent": "get-mlperf-inference-src,4b57186581024797 ( branch.master )"
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}
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},
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{
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"get,git,repo,_branch.master,_repo.https://github.com/mlcommons/inference": {
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"script_uid": "ed603e7292974f10",
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"script_alias": "get-git-repo",
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"script_tags": "get,git,repo,repository,clone",
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"script_variations": "branch.master,repo.https://github.com/mlcommons/inference",
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"version": "",
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"parent": "get-mlperf-inference-src,4b57186581024797 ( branch.master )"
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}
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{
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"get,mlcommons,inference,src,_branch.master": {
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"script_uid": "4b57186581024797",
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"script_alias": "get-mlperf-inference-src",
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"script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
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"script_variations": "",
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"version": "master-git-0a3570efb0309b5581f2831d84c05fe5483b5ef7",
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"script_variations": "branch.master",
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"version": "custom-git-0a3570efb0309b5581f2831d84c05fe5483b5ef7",
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"parent": "app-mlperf-inference,d775cac873ee4231 ( cpp,_retinanet,_onnxruntime,_cpu,_test,_r5.1-dev_default,_offline )"
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}
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},
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{
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"get,mlperf,inference,src": {
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"get,mlperf,inference,src,_branch.master": {
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"script_uid": "4b57186581024797",
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"script_alias": "get-mlperf-inference-src",
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"script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
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"script_variations": "",
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"version": "master-git-0a3570efb0309b5581f2831d84c05fe5483b5ef7",
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"script_variations": "branch.master",
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"version": "custom-git-0a3570efb0309b5581f2831d84c05fe5483b5ef7",
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"parent": "get-mlperf-inference-utils,e341e5f86d8342e5"
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}
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},
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}
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},
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{
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"get,mlcommons,inference,src": {
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"get,mlcommons,inference,src,_branch.master": {
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"script_uid": "4b57186581024797",
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"script_alias": "get-mlperf-inference-src",
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"script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
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"script_variations": "",
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"version": "master-git-0a3570efb0309b5581f2831d84c05fe5483b5ef7",
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"script_variations": "branch.master",
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"version": "custom-git-0a3570efb0309b5581f2831d84c05fe5483b5ef7",
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"parent": "app-mlperf-inference-mlcommons-cpp,bf62405e6c7a44bf ( offline,_retinanet,_onnxruntime,_cpu )"
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}
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},
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}
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},
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{
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"get,mlcommons,inference,src": {
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"get,mlcommons,inference,src,_branch.master": {
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"script_uid": "4b57186581024797",
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"script_alias": "get-mlperf-inference-src",
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"script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
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"version": "master-git-0a3570efb0309b5581f2831d84c05fe5483b5ef7",
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"script_variations": "branch.master",
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"version": "custom-git-0a3570efb0309b5581f2831d84c05fe5483b5ef7",
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"parent": "generate-mlperf-inference-user-conf,3af4475745964b93 ( wg-inference )"
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}
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},

‎open/MLCommons/measurements/default-mlcommons_cpp-cpu-onnxruntime-default_config/retinanet/offline/os_info.json

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"MLC_HOST_PYTHON_BITS": "64",
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"MLC_HOST_SYSTEM_NAME": "pkrvmbietmlfzoi",
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"+PATH": [
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"/home/runner/MLC/repos/local/cache/install-python-src_ffdc2dc4/install/bin"
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"/home/runner/MLC/repos/local/cache/install-python-src_9818ad19/install/bin"
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]
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}

‎open/MLCommons/measurements/default-mlcommons_cpp-cpu-onnxruntime-default_config/retinanet/offline/performance_console.out

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User Conf path: /home/runner/MLC/repos/anandhu-eng@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/f803f54edae24a2d8824f9669c1f307f.conf
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Dataset Preprocessed path: /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-openimages_84cef78e
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Dataset List filepath: /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-openimages_84cef78e/annotations/openimages-mlperf.json
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User Conf path: /home/runner/MLC/repos/GATEOverflow@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/e6a5edc91faf44df999a0dede8c69bfb.conf
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Dataset Preprocessed path: /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-openimages_dea2dee8
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Dataset List filepath: /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-openimages_dea2dee8/annotations/openimages-mlperf.json
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Scenario: Offline
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Mode: PerformanceOnly
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Batch size: 1

‎open/MLCommons/results/default-mlcommons_cpp-cpu-onnxruntime-default_config/retinanet/offline/accuracy/accuracy.txt

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found 0 images with no results
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ignored 0 dupes
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hash=cb1bf65db8a0d1283a6d4c822731317398434e1c568147840ce8ee40a5a3823b

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