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Results from Retinanet GH action on windows-latest
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‎open/MLCommons/measurements/gh_windows-latest-reference-cpu-pytorch_v2.4.1-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 | 76.951 | 0.318 | - |
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| retinanet | offline | 76.951 | 0.316 | - |

‎open/MLCommons/measurements/gh_windows-latest-reference-cpu-pytorch_v2.4.1-default_config/retinanet/offline/README.md

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* OS version: Windows-2022Server-10.0.20348-SP0
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* CPU version: AMD64 Family 25 Model 1 Stepping 1, AuthenticAMD
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* Python version: 3.12.7 (tags/v3.12.7:0b05ead, Oct 1 2024, 03:06:41) [MSC v.1941 64 bit (AMD64)]
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* MLCommons CM version: 3.0.4
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* MLCommons CM version: 3.2.1
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## CM Run Command
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cm rm cache -f
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cm pull repo anandhu-eng@cm4mlops --checkout=4990504f0b834ae59336aa362598b71ae5d33862
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cm pull repo anandhu-eng@cm4mlops --checkout=6c2c8f4c62442ebef7163876d85aa1ec84f72435
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cm run script ^
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--tags=run,mlperf,inference,generate-run-cmds,_submission,_short ^
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`mAP`: `76.951`, Required accuracy for closed division `>= 37.1745`
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### Performance Results
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`Samples per second`: `0.317954`
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`Samples per second`: `0.315732`

‎open/MLCommons/measurements/gh_windows-latest-reference-cpu-pytorch_v2.4.1-default_config/retinanet/offline/cm-version-info.json

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‎open/MLCommons/measurements/gh_windows-latest-reference-cpu-pytorch_v2.4.1-default_config/retinanet/offline/os_info.json

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"CM_HOST_OS_PACKAGE_MANAGER_INSTALL_CMD": "choco install -y",
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‎open/MLCommons/measurements/gh_windows-latest-reference-cpu-pytorch_v2.4.1-default_config/retinanet/offline/pip_freeze.json

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{
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‎open/MLCommons/model_mapping.json

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"retinanet": "retinanet"
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