Results from R50 GH action on

Author: mlcommons-bot

open/MLCommons/measurements/gh_ubuntu-latest-reference-cpu-tvm-onnx_v1.19.2-default_config/README.md

@@ -1,3 +1,3 @@
 | Model    | Scenario   |   Accuracy |   Throughput | Latency (in ms)   |
 |----------|------------|------------|--------------|-------------------|
-| resnet50 | offline    |         80 |        1.747 | -                 |
+| resnet50 | offline    |         80 |        1.745 | -                 |

open/MLCommons/measurements/gh_ubuntu-latest-reference-cpu-tvm-onnx_v1.19.2-default_config/resnet50/offline/README.md

@@ -17,16 +17,16 @@ pip install -U mlcflow
 
 mlc rm cache -f
 
-mlc pull repo GATEOverflow@mlperf-automations --checkout=1a3a286487c9a42205096e47591f46882656988e
+mlc pull repo anandhu-eng@mlperf-automations --checkout=0c4eedc30914c6404a02fbec2287ca0ecb4316e0
 
 
 ```
 *Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf,
- you should simply reload GATEOverflow@mlperf-automations without checkout and clean MLC cache as follows:*
+ you should simply reload anandhu-eng@mlperf-automations without checkout and clean MLC cache as follows:*
 
 ```bash
-mlc rm repo GATEOverflow@mlperf-automations
-mlc pull repo GATEOverflow@mlperf-automations
+mlc rm repo anandhu-eng@mlperf-automations
+mlc pull repo anandhu-eng@mlperf-automations
 mlc rm cache -f
 
 ```
@@ -41,4 +41,4 @@ Model Precision: fp32
 `acc`: `80.0`, Required accuracy for closed division `>= 75.6954`
 
 ### Performance Results 
-`Samples per second`: `1.74719`
+`Samples per second`: `1.74508`

open/MLCommons/measurements/gh_ubuntu-latest-reference-cpu-tvm-onnx_v1.19.2-default_config/resnet50/offline/accuracy_console.out

@@ -1,10 +1,10 @@
-python3 python/main.py --profile resnet50-onnxruntime --model "/home/runner/MLC/repos/local/cache/get-tvm-model_ac1d9fce/resnet50_v1.onnx" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_b7a2c1b7 --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_d34641cd/test_results/gh_ubuntu-latest-reference-cpu-tvm-onnx-v1.19.2-default_config/resnet50/offline/accuracy" --backend tvm --scenario Offline --max-batchsize 1 --count 5 --threads 4 --user_conf /home/runner/MLC/repos/GATEOverflow@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/c71d9e1e3a1e4348953df7d225314238.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_b7a2c1b7 --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_7c981d10/val.txt
-INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_b7a2c1b7', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_7c981d10/val.txt', data_format=None, profile='resnet50-onnxruntime', scenario='Offline', max_batchsize=1, model='/home/runner/MLC/repos/local/cache/get-tvm-model_ac1d9fce/resnet50_v1.onnx', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_d34641cd/test_results/gh_ubuntu-latest-reference-cpu-tvm-onnx-v1.19.2-default_config/resnet50/offline/accuracy', inputs=None, outputs=['ArgMax:0'], backend='tvm', device=None, model_name='resnet50', threads=4, qps=None, cache=0, cache_dir='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_b7a2c1b7', preprocessed_dir=None, use_preprocessed_dataset=True, accuracy=True, find_peak_performance=False, debug=False, user_conf='/home/runner/MLC/repos/GATEOverflow@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/c71d9e1e3a1e4348953df7d225314238.conf', audit_conf='audit.config', time=None, count=5, performance_sample_count=None, max_latency=None, samples_per_query=8)
+python3 python/main.py --profile resnet50-onnxruntime --model "/home/runner/MLC/repos/local/cache/get-tvm-model_50f6a5a6/resnet50_v1.onnx" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_e3b72127 --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_55329b99/test_results/gh_ubuntu-latest-reference-cpu-tvm-onnx-v1.19.2-default_config/resnet50/offline/accuracy" --backend tvm --scenario Offline --max-batchsize 1 --count 5 --threads 4 --user_conf /home/runner/MLC/repos/anandhu-eng@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/1f197114a6fb4f8583c60126a632f9f0.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_e3b72127 --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_2c3ca237/val.txt --max-batchsize 1
+INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_e3b72127', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_2c3ca237/val.txt', data_format=None, profile='resnet50-onnxruntime', scenario='Offline', max_batchsize=1, model='/home/runner/MLC/repos/local/cache/get-tvm-model_50f6a5a6/resnet50_v1.onnx', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_55329b99/test_results/gh_ubuntu-latest-reference-cpu-tvm-onnx-v1.19.2-default_config/resnet50/offline/accuracy', inputs=None, outputs=['ArgMax:0'], backend='tvm', device=None, model_name='resnet50', threads=4, qps=None, cache=0, cache_dir='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_e3b72127', preprocessed_dir=None, use_preprocessed_dataset=True, accuracy=True, find_peak_performance=False, debug=False, user_conf='/home/runner/MLC/repos/anandhu-eng@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/1f197114a6fb4f8583c60126a632f9f0.conf', audit_conf='audit.config', time=None, count=5, performance_sample_count=None, max_latency=None, samples_per_query=8)
 INFO:imagenet:Loading 5 preprocessed images using 4 threads
 INFO:imagenet:loaded 5 images, cache=0, already_preprocessed=True, took=0.0sec
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_ac1d9fce/model-tvm.so
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_50f6a5a6/model-tvm.so
 INFO:main:starting TestScenario.Offline
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_ac1d9fce/model-tvm.so
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_ac1d9fce/model-tvm.so
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_ac1d9fce/model-tvm.so
-TestScenario.Offline qps=1.72, mean=1.7595, time=2.909, acc=80.000%, queries=5, tiles=50.0:1.4860,80.0:1.7698,90.0:2.3261,95.0:2.6042,99.0:2.8267,99.9:2.8768
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_50f6a5a6/model-tvm.so
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_50f6a5a6/model-tvm.so
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_50f6a5a6/model-tvm.so
+TestScenario.Offline qps=1.72, mean=1.7655, time=2.900, acc=80.000%, queries=5, tiles=50.0:1.4936,80.0:1.7965,90.0:2.3353,95.0:2.6046,99.0:2.8202,99.9:2.8686