Auto-merge updates from auto-update branch

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 |        1.743 | -                 |
+| resnet50 | offline    |         80 |        1.737 | -                 |

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 anandhu-eng@mlperf-automations --checkout=522ca999af25f441b54de09f21aa00fed823d89a
+mlc pull repo mlcommons@mlperf-automations --checkout=6a523e3aa6ca08eef566451562ea0a3950e73e04
 
 
 ```
 *Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf,
- you should simply reload anandhu-eng@mlperf-automations without checkout and clean MLC cache as follows:*
+ you should simply reload mlcommons@mlperf-automations without checkout and clean MLC cache as follows:*
 
 ```bash
-mlc rm repo anandhu-eng@mlperf-automations
-mlc pull repo anandhu-eng@mlperf-automations
+mlc rm repo mlcommons@mlperf-automations
+mlc pull repo mlcommons@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`: `1.74283`
+`Samples per second`: `1.73713`

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

@@ -1,11 +1,10 @@
-python3 python/main.py --profile resnet50-onnxruntime --model "/home/runner/MLC/repos/local/cache/get-tvm-model_f00ddb90/resnet50_v1.onnx" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_21255848 --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_d58e91c6/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/3726c9c5dc284142860d04a12c58126d.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_21255848 --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_4578fabb/val.txt
-INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_21255848', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_4578fabb/val.txt', data_format=None, profile='resnet50-onnxruntime', scenario='Offline', max_batchsize=1, model='/home/runner/MLC/repos/local/cache/get-tvm-model_f00ddb90/resnet50_v1.onnx', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_d58e91c6/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_21255848', 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/3726c9c5dc284142860d04a12c58126d.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_c07c015e/resnet50_v1.onnx" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_73de9fff --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_b3d533c1/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/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5f3171931a9a46b596cea09f123667f5.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_73de9fff --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_cdbfd929/val.txt
+INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_73de9fff', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_cdbfd929/val.txt', data_format=None, profile='resnet50-onnxruntime', scenario='Offline', max_batchsize=1, model='/home/runner/MLC/repos/local/cache/get-tvm-model_c07c015e/resnet50_v1.onnx', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_b3d533c1/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_73de9fff', preprocessed_dir=None, use_preprocessed_dataset=True, accuracy=True, find_peak_performance=False, debug=False, user_conf='/home/runner/MLC/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/5f3171931a9a46b596cea09f123667f5.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_f00ddb90/model-tvm.so
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_c07c015e/model-tvm.so
 INFO:main:starting TestScenario.Offline
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_f00ddb90/model-tvm.so
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_f00ddb90/model-tvm.so
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_f00ddb90/model-tvm.so
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_f00ddb90/model-tvm.so
-TestScenario.Offline qps=1.73, mean=1.7562, time=2.893, acc=80.000%, queries=5, tiles=50.0:1.4816,80.0:1.7695,90.0:2.3184,95.0:2.5928,99.0:2.8124,99.9:2.8618
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_c07c015e/model-tvm.so
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_c07c015e/model-tvm.so
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_c07c015e/model-tvm.so
+TestScenario.Offline qps=1.73, mean=1.7688, time=2.892, acc=80.000%, queries=5, tiles=50.0:1.4934,80.0:1.7990,90.0:2.3345,95.0:2.6022,99.0:2.8164,99.9:2.8646