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Results on UCSD 2 Nodes of 4x MI210 #85

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2 changes: 1 addition & 1 deletion ...easurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/README.md
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@@ -1,3 +1,3 @@
| Model | Scenario | Accuracy | Throughput | Latency (in ms) |
|---------------------|------------|----------------------|--------------|-------------------|
| stable-diffusion-xl | offline | (15.22477, 84.24318) | 0.848 | - |
| stable-diffusion-xl | offline | (15.22522, 84.25505) | 1.578 | - |
9 changes: 5 additions & 4 deletions ...ocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/README.md
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Expand Up @@ -33,7 +33,8 @@ cm run script \
--adr.mlperf-implementation.tags=_branch.multinode-test,_repo.https://github.com/zixianwang2022/mlperf-scc24 \
--adr.mlperf-implementation.version=custom \
--env.CM_GET_PLATFORM_DETAILS=no \
--target_qps=1.8
--target_qps=1.8 \
--rerun
```
*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts),
you should simply reload mlcommons@cm4mlops without checkout and clean CM cache as follows:*
Expand All @@ -52,8 +53,8 @@ Platform: aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main
Model Precision: fp32

### Accuracy Results
`CLIP_SCORE`: `15.22477`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332`
`FID_SCORE`: `84.24318`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008`
`CLIP_SCORE`: `15.22522`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332`
`FID_SCORE`: `84.25505`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008`

### Performance Results
`Samples per second`: `0.847525`
`Samples per second`: `1.5779`
9 changes: 5 additions & 4 deletions ...cm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy_console.out
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INFO:main:Namespace(sut_server=['http://10.0.0.14:8008', 'http://10.0.0.12:8008'], dataset='coco-1024', dataset_path='/root/CM/repos/local/cache/61dd835801c542a3/install', profile='stable-diffusion-xl-pytorch', scenario='Offline', max_batchsize=1, threads=1, accuracy=True, find_peak_performance=False, backend='pytorch', model_name='stable-diffusion-xl', output='/root/CM/repos/local/cache/d549713c4a534705/test_results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy', qps=None, model_path='/root/CM/repos/local/cache/c4b6bbbebe504f28/stable_diffusion_fp16', dtype='fp16', device='cuda', latent_framework='torch', mlperf_conf='mlperf.conf', user_conf='/root/CM/repos/mlcommons@cm4mlops/script/generate-mlperf-inference-user-conf/tmp/6626c9658bff4d2291e3121038a4cfca.conf', audit_conf='audit.config', ids_path='/root/CM/repos/local/cache/61dd835801c542a3/install/sample_ids.txt', time=None, count=10, debug=False, performance_sample_count=5000, max_latency=None, samples_per_query=8)
INFO:main:Namespace(sut_server=['http://10.0.0.14:8008', 'http://10.0.0.12:8008'], dataset='coco-1024', dataset_path='/root/CM/repos/local/cache/61dd835801c542a3/install', profile='stable-diffusion-xl-pytorch', scenario='Offline', max_batchsize=1, threads=1, accuracy=True, find_peak_performance=False, backend='pytorch', model_name='stable-diffusion-xl', output='/root/CM/repos/local/cache/d549713c4a534705/test_results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy', qps=None, model_path='/root/CM/repos/local/cache/c4b6bbbebe504f28/stable_diffusion_fp16', dtype='fp16', device='cuda', latent_framework='torch', mlperf_conf='mlperf.conf', user_conf='/root/CM/repos/mlcommons@cm4mlops/script/generate-mlperf-inference-user-conf/tmp/1608e150c4d94edb9537a0fe9198425f.conf', audit_conf='audit.config', ids_path='/root/CM/repos/local/cache/61dd835801c542a3/install/sample_ids.txt', time=None, count=10, debug=False, performance_sample_count=5000, max_latency=None, samples_per_query=8)
WARNING:backend-pytorch:Model path not provided, running with default hugging face weights
This may not be valid for official submissions
Keyword arguments {'safety_checker': None} are not expected by StableDiffusionXLPipeline and will be ignored.
Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]Using the `SDPA` attention implementation on multi-gpu setup with ROCM may lead to performance issues due to the FA backend. Disabling it to use alternative backends.
Loading pipeline components...: 57%|█████▋ | 4/7 [00:00<00:00, 12.44it/s]Loading pipeline components...: 86%|████████▌ | 6/7 [00:00<00:00, 7.56it/s]Loading pipeline components...: 100%|██████████| 7/7 [00:00<00:00, 9.15it/s]
RETURNED from requests.post on predict at time 1731969667.0400865
Loading pipeline components...: 57%|█████▋ | 4/7 [00:00<00:00, 16.65it/s]Loading pipeline components...: 86%|████████▌ | 6/7 [00:00<00:00, 11.90it/s]Loading pipeline components...: 100%|██████████| 7/7 [00:00<00:00, 10.73it/s]
:::MLLOG {"key": "error_invalid_config", "value": "Multiple conf files are used. This is not valid for official submission.", "time_ms": 1732142436869.237178, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": true, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 539, "pid": 30316, "tid": 30316}}
RETURNED from requests.post on predict at time 1732142751.4806168
BEFORE lg.QuerySamplesComplete(response)
AFTER lg.QuerySamplesComplete(response)
RETURNED from requests.post on predict at time 1731969689.698808
RETURNED from requests.post on predict at time 1732142752.913671
BEFORE lg.QuerySamplesComplete(response)
AFTER lg.QuerySamplesComplete(response)
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