Results from R50 GH action

open/MLCommons/code/resnet50/README.md

@@ -0,0 +1 @@
+TBD

open/MLCommons/measurements/gh_ubuntu-latest_x86-mlcommons_cpp-cpu-onnxruntime-default_config/README.md

@@ -0,0 +1,3 @@
+| Model    | Scenario   |   Accuracy |   Throughput | Latency (in ms)   |
+|----------|------------|------------|--------------|-------------------|
+| resnet50 | offline    |         76 |       23.161 | -                 |

open/MLCommons/measurements/gh_ubuntu-latest_x86-mlcommons_cpp-cpu-onnxruntime-default_config/resnet50/offline/README.md

@@ -0,0 +1,57 @@
+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-6.8.0-1014-azure-x86_64-with-glibc2.35
+* CPU version: x86_64
+* Python version: 3.12.6 (main, Sep  9 2024, 03:08:08) [GCC 11.4.0]
+* MLCommons CM version: 2.3.9
+
+## 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 anandhu-eng@cm4mlops --checkout=4b083d3814e998892d58a72f98477a46b65b8165
+
+cm run script \
+	--tags=run-mlperf,inference,_submission,_short \
+	--submitter=MLCommons \
+	--hw_name=gh_ubuntu-latest_x86 \
+	--model=resnet50 \
+	--implementation=cpp \
+	--backend=onnxruntime \
+	--device=cpu \
+	--scenario=Offline \
+	--test_query_count=500 \
+	--target_qps=1 \
+	-v \
+	--quiet
+```
+*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts),
+ you should simply reload anandhu-eng@cm4mlops without checkout and clean CM cache as follows:*
+
+```bash
+cm rm repo anandhu-eng@cm4mlops
+cm pull repo anandhu-eng@cm4mlops
+cm rm cache -f
+
+```
+
+## Results
+
+Platform: gh_ubuntu-latest_x86-mlcommons_cpp-cpu-onnxruntime-default_config
+
+Model Precision: fp32
+
+### Accuracy Results 
+`acc`: `76.0`, Required accuracy for closed division `>= 75.6954`
+
+### Performance Results 
+`Samples per second`: `23.1609`