From 17d0014a22cb3facd7791abb357f6023709e04d6 Mon Sep 17 00:00:00 2001 From: Arjun Suresh Date: Tue, 19 Nov 2024 17:23:33 +0530 Subject: [PATCH] Results from self hosted Github actions - NVIDIARTX4090 --- .../README.md | 3 + .../stable-diffusion-xl/offline/README.md | 100 + .../offline/accuracy_console.out | 68 + ...e-gpu-pytorch-v2.5.1-scc24-base_cu124.json | 7 + .../offline/cm-version-info.json | 614 ++++ .../stable-diffusion-xl/offline/cpu_info.json | 27 + .../stable-diffusion-xl/offline/mlperf.conf | 98 + .../offline/model-info.json | 7 + .../stable-diffusion-xl/offline/os_info.json | 30 + .../offline/performance_console.out | 61 + .../offline/pip_freeze.json | 73 + .../offline/system_info.txt | 2765 +++++++++++++++++ .../stable-diffusion-xl/offline/user.conf | 5 + .../stable-diffusion-xl/system_info.txt | 2765 +++++++++++++++++ .../system_info.txt | 2765 +++++++++++++++++ .../offline/accuracy/accuracy.txt | 2 + .../offline/accuracy/images/1.png | Bin 0 -> 2177409 bytes 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open/MLCommons/results/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt create mode 100644 open/MLCommons/results/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt create mode 100644 open/MLCommons/systems/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124.json diff --git a/open/MLCommons/measurements/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/README.md b/open/MLCommons/measurements/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/README.md new file mode 100644 index 0000000..75e88af --- /dev/null +++ b/open/MLCommons/measurements/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/README.md @@ -0,0 +1,3 @@ +| Model | Scenario | Accuracy | Throughput | Latency (in ms) | +|---------------------|------------|----------------------|--------------|-------------------| +| stable-diffusion-xl | offline | (16.3689, 237.82579) | 0.383 | - | \ No newline at end of file diff --git a/open/MLCommons/measurements/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/stable-diffusion-xl/offline/README.md b/open/MLCommons/measurements/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/stable-diffusion-xl/offline/README.md new file mode 100644 index 0000000..f09172c --- /dev/null +++ b/open/MLCommons/measurements/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/stable-diffusion-xl/offline/README.md @@ -0,0 +1,100 @@ +This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops). + +*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.* + +## Host platform + +* OS version: Linux-6.2.0-39-generic-x86_64-with-glibc2.35 +* CPU version: x86_64 +* Python version: 3.10.12 (main, Sep 11 2024, 15:47:36) [GCC 11.4.0] +* MLCommons CM version: 3.3.4 + +## CM Run Command + +See [CM installation guide](https://docs.mlcommons.org/inference/install/). + +```bash +pip install -U cmind + +cm rm cache -f + +cm pull repo gateoverflow@cm4mlops --checkout=09f0cdbcd4f25c5929e9e6a4bc96bb31ab956d23 + +cm run script \ + --tags=app,mlperf,inference,generic,_reference,_sdxl,_pytorch,_cuda,_test,_r4.1-dev_default,_float16,_offline \ + --quiet=true \ + --env.CM_MLPERF_MODEL_SDXL_DOWNLOAD_TO_HOST=yes \ + --env.CM_QUIET=yes \ + --env.CM_MLPERF_IMPLEMENTATION=reference \ + --env.CM_MLPERF_MODEL=sdxl \ + --env.CM_MLPERF_RUN_STYLE=test \ + --env.CM_MLPERF_SKIP_SUBMISSION_GENERATION=False \ + --env.CM_DOCKER_PRIVILEGED_MODE=True \ + --env.CM_MLPERF_BACKEND=pytorch \ + --env.CM_MLPERF_SUBMISSION_SYSTEM_TYPE=datacenter \ + --env.CM_MLPERF_CLEAN_ALL=True \ + --env.CM_MLPERF_DEVICE=cuda \ + --env.CM_MLPERF_USE_DOCKER=True \ + --env.CM_MLPERF_MODEL_PRECISION=float16 \ + --env.OUTPUT_BASE_DIR=/home/arjun/scc_gh_action_results \ + --env.CM_MLPERF_LOADGEN_SCENARIO=Offline \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/home/arjun/scc_gh_action_submissions \ + --env.CM_MLPERF_INFERENCE_VERSION=4.1-dev \ + --env.CM_RUN_MLPERF_INFERENCE_APP_DEFAULTS=r4.1-dev_default \ + --env.CM_MLPERF_SUBMISSION_GENERATION_STYLE=short \ + --env.CM_MLPERF_SUT_NAME_RUN_CONFIG_SUFFIX4=scc24-base \ + --env.CM_DOCKER_IMAGE_NAME=scc24-reference \ + --env.CM_MLPERF_INFERENCE_MIN_QUERY_COUNT=50 \ + --env.CM_MLPERF_LOADGEN_ALL_MODES=yes \ + --env.CM_MLPERF_INFERENCE_SOURCE_VERSION=4.1.23 \ + --env.CM_MLPERF_LAST_RELEASE=v4.1 \ + --env.CM_TMP_CURRENT_PATH=/home/arjun/actions-runner/_work/cm4mlops/cm4mlops \ + --env.CM_TMP_PIP_VERSION_STRING= \ + --env.CM_MODEL=sdxl \ + --env.CM_MLPERF_LOADGEN_COMPLIANCE=no \ + --env.CM_MLPERF_CLEAN_SUBMISSION_DIR=yes \ + --env.CM_RERUN=yes \ + --env.CM_MLPERF_LOADGEN_EXTRA_OPTIONS= \ + --env.CM_MLPERF_LOADGEN_MODE=performance \ + --env.CM_MLPERF_LOADGEN_SCENARIOS,=Offline \ + --env.CM_MLPERF_LOADGEN_MODES,=performance,accuracy \ + --env.CM_OUTPUT_FOLDER_NAME=test_results \ + --env.CM_DOCKER_REUSE_EXISTING_CONTAINER=no \ + --env.CM_DOCKER_DETACHED_MODE=yes \ + --add_deps_recursive.get-mlperf-inference-results-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.get-mlperf-inference-submission-dir.tags=_version.r4_1-dev \ + --add_deps_recursive.mlperf-inference-nvidia-scratch-space.tags=_version.r4_1-dev \ + --add_deps_recursive.submission-checker.tags=_short-run \ + --add_deps_recursive.coco2014-preprocessed.tags=_size.50,_with-sample-ids \ + --add_deps_recursive.coco2014-dataset.tags=_size.50,_with-sample-ids \ + --add_deps_recursive.nvidia-preprocess-data.extra_cache_tags=scc24-base \ + --v=False \ + --print_env=False \ + --print_deps=False \ + --dump_version_info=True \ + --env.OUTPUT_BASE_DIR=/cm-mount/home/arjun/scc_gh_action_results \ + --env.CM_MLPERF_INFERENCE_SUBMISSION_DIR=/cm-mount/home/arjun/scc_gh_action_submissions \ + --env.SDXL_CHECKPOINT_PATH=/home/cmuser/CM/repos/local/cache/6be1f30ecbde4c4e/stable_diffusion_fp16 +``` +*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts), + you should simply reload gateoverflow@cm4mlops without checkout and clean CM cache as follows:* + +```bash +cm rm repo gateoverflow@cm4mlops +cm pull repo gateoverflow@cm4mlops +cm rm cache -f + +``` + +## Results + +Platform: c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124 + +Model Precision: fp32 + +### Accuracy Results +`CLIP_SCORE`: `16.3689`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332` +`FID_SCORE`: `237.82579`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008` + +### Performance Results +`Samples per second`: `0.383379` diff --git a/open/MLCommons/measurements/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/stable-diffusion-xl/offline/accuracy_console.out b/open/MLCommons/measurements/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/stable-diffusion-xl/offline/accuracy_console.out new file mode 100644 index 0000000..73402a8 --- /dev/null +++ b/open/MLCommons/measurements/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/stable-diffusion-xl/offline/accuracy_console.out @@ -0,0 +1,68 @@ +INFO:main:Namespace(dataset='coco-1024', dataset_path='/home/cmuser/CM/repos/local/cache/0fd744f4046f4dae/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='/cm-mount/home/arjun/scc_gh_action_results/test_results/c305c362b2a3-reference-gpu-pytorch-v2.5.1-scc24-base_cu124/stable-diffusion-xl/offline/accuracy', qps=None, model_path='/home/cmuser/CM/repos/local/cache/6be1f30ecbde4c4e/stable_diffusion_fp16', dtype='fp16', device='cuda', latent_framework='torch', 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