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Results from self hosted Github actions - NVIDIARTX4090
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arjunsuresh committed Nov 26, 2024
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| Model | Scenario | Accuracy | Throughput | Latency (in ms) |
|---------------------|------------|---------------------|--------------|-------------------|
| stable-diffusion-xl | offline | (31.2817, 23.34533) | 1.312 | - |
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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-glibc2.29
* CPU version: x86_64
* Python version: 3.8.10 (default, Sep 11 2024, 16:02:53)
[GCC 9.4.0]
* 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=ea6a31007f0354c5548a8c5d75ab2911f8b070bd

cm run script \
--tags=app,mlperf,inference,generic,_nvidia,_sdxl,_tensorrt,_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=nvidia \
--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=tensorrt \
--env.CM_MLPERF_SUBMISSION_SYSTEM_TYPE=datacenter \
--env.CM_MLPERF_CLEAN_ALL=True \
--env.CM_MLPERF_DEVICE= \
--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_DIVISION=open \
--env.CM_RUN_MLPERF_SUBMISSION_PREPROCESSOR=False \
--env.CM_MLPERF_SUBMISSION_GENERATION_STYLE=short \
--env.CM_MLPERF_SUT_NAME_RUN_CONFIG_SUFFIX4=scc24-base \
--env.CM_DOCKER_IMAGE_NAME=scc24-nvidia \
--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 \
--env.MLPERF_SCRATCH_PATH=/home/cmuser/CM/repos/local/cache/e066920512fd47b7
```
*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: ce80516ed769-nvidia_original-gpu-tensorrt-vdefault-scc24-base

Model Precision: int8

### Accuracy Results
`CLIP_SCORE`: `31.2817`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332`
`FID_SCORE`: `23.34533`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008`

### Performance Results
`Samples per second`: `1.31223`
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[2024-11-25 19:55:53,319 main.py:229 INFO] Detected system ID: KnownSystem.ce80516ed769
/home/cmuser/.local/lib/python3.8/site-packages/torchvision/datapoints/__init__.py:12: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().
warnings.warn(_BETA_TRANSFORMS_WARNING)
/home/cmuser/.local/lib/python3.8/site-packages/torchvision/transforms/v2/__init__.py:54: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().
warnings.warn(_BETA_TRANSFORMS_WARNING)
[2024-11-25 19:55:54,884 generate_conf_files.py:107 INFO] Generated measurements/ entries for ce80516ed769_TRT/stable-diffusion-xl/Offline
[2024-11-25 19:55:54,885 __init__.py:46 INFO] Running command: python3 -m code.stable-diffusion-xl.tensorrt.harness --logfile_outdir="/cm-mount/home/arjun/scc_gh_action_results/test_results/ce80516ed769-nvidia_original-gpu-tensorrt-vdefault-scc24-base/stable-diffusion-xl/offline/accuracy" --logfile_prefix="mlperf_log_" --performance_sample_count=5000 --test_mode="AccuracyOnly" --gpu_batch_size=2 --mlperf_conf_path="/home/cmuser/CM/repos/local/cache/2ef781707c5b4033/inference/mlperf.conf" --tensor_path="build/preprocessed_data/coco2014-tokenized-sdxl/5k_dataset_final/" --use_graphs=false --user_conf_path="/home/cmuser/CM/repos/gateoverflow@cm4mlops/script/generate-mlperf-inference-user-conf/tmp/56a430acc74642cd88099b90dfbd1a9c.conf" --gpu_inference_streams=1 --gpu_copy_streams=1 --gpu_engines="./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-CLIP-Offline-gpu-b2-fp16.custom_k_99_MaxP.plan,./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-CLIPWithProj-Offline-gpu-b2-fp16.custom_k_99_MaxP.plan,./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-UNetXL-Offline-gpu-b2-int8.custom_k_99_MaxP.plan,./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-VAE-Offline-gpu-b2-fp32.custom_k_99_MaxP.plan" --scenario Offline --model stable-diffusion-xl
[2024-11-25 19:55:54,885 __init__.py:53 INFO] Overriding Environment
/home/cmuser/.local/lib/python3.8/site-packages/torchvision/datapoints/__init__.py:12: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().
warnings.warn(_BETA_TRANSFORMS_WARNING)
/home/cmuser/.local/lib/python3.8/site-packages/torchvision/transforms/v2/__init__.py:54: UserWarning: The torchvision.datapoints and torchvision.transforms.v2 namespaces are still Beta. While we do not expect major breaking changes, some APIs may still change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753, and you can also check out https://github.com/pytorch/vision/issues/7319 to learn more about the APIs that we suspect might involve future changes. You can silence this warning by calling torchvision.disable_beta_transforms_warning().
warnings.warn(_BETA_TRANSFORMS_WARNING)
[2024-11-25 19:55:56,681 backend.py:71 INFO] Loading TensorRT engine: ./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-CLIP-Offline-gpu-b2-fp16.custom_k_99_MaxP.plan.
[2024-11-25 19:55:56,828 backend.py:71 INFO] Loading TensorRT engine: ./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-CLIPWithProj-Offline-gpu-b2-fp16.custom_k_99_MaxP.plan.
[2024-11-25 19:55:57,554 backend.py:71 INFO] Loading TensorRT engine: ./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-UNetXL-Offline-gpu-b2-int8.custom_k_99_MaxP.plan.
[2024-11-25 19:55:58,972 backend.py:71 INFO] Loading TensorRT engine: ./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-VAE-Offline-gpu-b2-fp32.custom_k_99_MaxP.plan.
[2024-11-25 19:56:00,395 backend.py:71 INFO] Loading TensorRT engine: ./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-CLIP-Offline-gpu-b2-fp16.custom_k_99_MaxP.plan.
[2024-11-25 19:56:00,579 backend.py:71 INFO] Loading TensorRT engine: ./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-CLIPWithProj-Offline-gpu-b2-fp16.custom_k_99_MaxP.plan.
[2024-11-25 19:56:01,322 backend.py:71 INFO] Loading TensorRT engine: ./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-UNetXL-Offline-gpu-b2-int8.custom_k_99_MaxP.plan.
[2024-11-25 19:56:02,714 backend.py:71 INFO] Loading TensorRT engine: ./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-VAE-Offline-gpu-b2-fp32.custom_k_99_MaxP.plan.
[2024-11-25 19:56:03,929 harness.py:207 INFO] Start Warm Up!
[2024-11-25 19:56:15,762 harness.py:209 INFO] Warm Up Done!
[2024-11-25 19:56:15,763 harness.py:211 INFO] Start Test!
[2024-11-25 20:58:17,284 backend.py:801 INFO] [Server] Received 5000 total samples
[2024-11-25 20:58:17,284 backend.py:809 INFO] [Device 0] Reported 2496 samples
[2024-11-25 20:58:17,284 backend.py:809 INFO] [Device 1] Reported 2504 samples
[2024-11-25 20:58:17,284 harness.py:214 INFO] Test Done!
[2024-11-25 20:58:17,284 harness.py:216 INFO] Destroying SUT...
[2024-11-25 20:58:17,284 harness.py:219 INFO] Destroying QSL...
benchmark : Benchmark.SDXL
buffer_manager_thread_count : 0
data_dir : /home/cmuser/CM/repos/local/cache/e066920512fd47b7/data
gpu_batch_size : 2
gpu_copy_streams : 1
gpu_inference_streams : 1
input_dtype : int32
input_format : linear
log_dir : /home/cmuser/CM/repos/local/cache/e0e53f17cf2744e0/repo/closed/NVIDIA/build/logs/2024.11.25-19.55.52
mlperf_conf_path : /home/cmuser/CM/repos/local/cache/2ef781707c5b4033/inference/mlperf.conf
model_path : /home/cmuser/CM/repos/local/cache/e066920512fd47b7/models/SDXL/
offline_expected_qps : 0.0
precision : int8
preprocessed_data_dir : /home/cmuser/CM/repos/local/cache/e066920512fd47b7/preprocessed_data
scenario : Scenario.Offline
system : SystemConfiguration(host_cpu_conf=CPUConfiguration(layout={CPU(name='Intel(R) Xeon(R) w7-2495X', architecture=<CPUArchitecture.x86_64: AliasedName(name='x86_64', aliases=(), patterns=())>, core_count=24, threads_per_core=2): 1}), host_mem_conf=MemoryConfiguration(host_memory_capacity=Memory(quantity=197.330052, byte_suffix=<ByteSuffix.GB: (1000, 3)>, _num_bytes=197330052000), comparison_tolerance=0.05), accelerator_conf=AcceleratorConfiguration(layout=defaultdict(<class 'int'>, {GPU(name='NVIDIA GeForce RTX 4090', accelerator_type=<AcceleratorType.Discrete: AliasedName(name='Discrete', aliases=(), patterns=())>, vram=Memory(quantity=23.98828125, byte_suffix=<ByteSuffix.GiB: (1024, 3)>, _num_bytes=25757220864), max_power_limit=450.0, pci_id='0x268410DE', compute_sm=89): 1, GPU(name='NVIDIA GeForce RTX 4090', accelerator_type=<AcceleratorType.Discrete: AliasedName(name='Discrete', aliases=(), patterns=())>, vram=Memory(quantity=23.98828125, byte_suffix=<ByteSuffix.GiB: (1024, 3)>, _num_bytes=25757220864), max_power_limit=500.0, pci_id='0x268410DE', compute_sm=89): 1})), numa_conf=NUMAConfiguration(numa_nodes={}, num_numa_nodes=1), system_id='ce80516ed769')
tensor_path : build/preprocessed_data/coco2014-tokenized-sdxl/5k_dataset_final/
test_mode : AccuracyOnly
use_graphs : False
user_conf_path : /home/cmuser/CM/repos/gateoverflow@cm4mlops/script/generate-mlperf-inference-user-conf/tmp/56a430acc74642cd88099b90dfbd1a9c.conf
system_id : ce80516ed769
config_name : ce80516ed769_stable-diffusion-xl_Offline
workload_setting : WorkloadSetting(HarnessType.Custom, AccuracyTarget.k_99, PowerSetting.MaxP)
optimization_level : plugin-enabled
num_profiles : 1
config_ver : custom_k_99_MaxP
accuracy_level : 99%
inference_server : custom
skip_file_checks : False
power_limit : None
cpu_freq : None
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[W] Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
[I] Loading bytes from ./build/engines/ce80516ed769/stable-diffusion-xl/Offline/stable-diffusion-xl-CLIPWithProj-Offline-gpu-b2-fp16.custom_k_99_MaxP.plan
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[2024-11-25 20:58:17,833 run_harness.py:166 INFO] Result: Accuracy run detected.

======================== Result summaries: ========================

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{
"starting_weights_filename": "https://github.com/mlcommons/cm4mlops/blob/main/script/get-ml-model-stable-diffusion/_cm.json#L174",
"retraining": "no",
"input_data_types": "int32",
"weight_data_types": "int8",
"weight_transformations": "quantization, affine fusion"
}
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