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 |        1.725 | -                 |
+| resnet50 | offline    |         80 |        1.708 | -                 |

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=70c941bfd49c78b2e1d8343350a580cf73226f2d
+mlc pull repo anandhu-eng@mlperf-automations --checkout=4a0a38edd13eb7b049caa73ea13c644cbab819b2
 
 
 ```
 *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`: `1.72502`
+`Samples per second`: `1.7075`

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

@@ -1,11 +1,9 @@
-python3 python/main.py --profile resnet50-onnxruntime --model "/home/runner/MLC/repos/local/cache/get-tvm-model_b1c5a49b/resnet50_v1.onnx" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_225525d1 --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_45ddf402/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/bc1b7bc1a364484782bd5327129c363a.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_225525d1 --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_174b37c6/val.txt
-INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_225525d1', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_174b37c6/val.txt', data_format=None, profile='resnet50-onnxruntime', scenario='Offline', max_batchsize=1, model='/home/runner/MLC/repos/local/cache/get-tvm-model_b1c5a49b/resnet50_v1.onnx', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_45ddf402/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_225525d1', 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/bc1b7bc1a364484782bd5327129c363a.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_110b3007/resnet50_v1.onnx" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_ce1e3366 --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_98089ec2/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/73191e5f310940e1ac0ab61609884d1f.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_ce1e3366 --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_52ca3718/val.txt
+INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_ce1e3366', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_52ca3718/val.txt', data_format=None, profile='resnet50-onnxruntime', scenario='Offline', max_batchsize=1, model='/home/runner/MLC/repos/local/cache/get-tvm-model_110b3007/resnet50_v1.onnx', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_98089ec2/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_ce1e3366', 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/73191e5f310940e1ac0ab61609884d1f.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_b1c5a49b/model-tvm.so
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_110b3007/model-tvm.so
 INFO:main:starting TestScenario.Offline
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_b1c5a49b/model-tvm.so
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_b1c5a49b/model-tvm.so
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_b1c5a49b/model-tvm.so
-TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_b1c5a49b/model-tvm.so
-TestScenario.Offline qps=1.70, mean=1.7837, time=2.939, acc=80.000%, queries=5, tiles=50.0:1.5025,80.0:1.7861,90.0:2.3490,95.0:2.6304,99.0:2.8556,99.9:2.9062
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_110b3007/model-tvm.so
+TVM: loading model /home/runner/MLC/repos/local/cache/get-tvm-model_110b3007/model-tvm.so
+TestScenario.Offline qps=1.72, mean=1.7581, time=2.900, acc=80.000%, queries=5, tiles=50.0:1.4855,80.0:1.7657,90.0:2.3215,95.0:2.5994,99.0:2.8217,99.9:2.8717

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

@@ -20,6 +20,7 @@
   "MLC_HOST_CPU_L2_CACHE_SIZE": "1 MiB (2 instances)",
   "MLC_HOST_CPU_L3_CACHE_SIZE": "32 MiB (1 instance)",
   "MLC_HOST_CPU_NUMA_NODES": "1",
+  "MLC_HOST_CPU_START_CORES": "0",
   "MLC_HOST_CPU_TOTAL_LOGICAL_CORES": "4",
   "MLC_HOST_CPU_TOTAL_PHYSICAL_CORES": "2",
   "MLC_HOST_CPU_PHYSICAL_CORES_LIST": "0-1",