Merge pull request #1 from arjunsuresh/mlperf-inference-results-scc24

Results on system test

open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/README.md

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+| Model               | Scenario   | Accuracy              |   Throughput | Latency (in ms)   |
+|---------------------|------------|-----------------------|--------------|-------------------|
+| stable-diffusion-xl | offline    | (15.23624, 238.78369) |        0.374 | -                 |

open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base.json

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+{
+  "starting_weights_filename": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0",
+  "retraining": "no",
+  "input_data_types": "fp32",
+  "weight_data_types": "fp32",
+  "weight_transformations": "no"
+}

open/MLCommons/measurements/48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base/stable-diffusion-xl/offline/README.md

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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: 2.3.6
+
+## 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 mlcommons@cm4mlops --checkout=735b581a345d5a04f8cd7195f6fbff3a37c538d8
+
+cm run script \
+	--tags=run-mlperf,inference,_r4.1-dev,_short,_scc24-base \
+	--model=sdxl \
+	--implementation=reference \
+	--framework=pytorch \
+	--category=datacenter \
+	--scenario=Offline \
+	--execution_mode=test \
+	--device=cuda \
+	--quiet \
+	--precision=float16
+```
+*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:*
+
+```bash
+cm rm repo mlcommons@cm4mlops
+cm pull repo mlcommons@cm4mlops
+cm rm cache -f
+
+```
+
+## Results
+
+Platform: 48ed6105bd85-reference-gpu-pytorch_v2.1.0a0-scc24-base
+
+Model Precision: fp32
+
+### Accuracy Results 
+`CLIP_SCORE`: `15.23624`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332`
+`FID_SCORE`: `238.78369`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008`
+
+### Performance Results 
+`Samples per second`: `0.373636`