Skip to content

Commit 5a38799

Browse files
committed
Results from R50 GH action on ubuntu-latest
1 parent dc67340 commit 5a38799

File tree

14 files changed

+348
-347
lines changed

14 files changed

+348
-347
lines changed
Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,3 +1,3 @@
11
| Model | Scenario | Accuracy | Throughput | Latency (in ms) |
22
|----------|------------|------------|--------------|-------------------|
3-
| resnet50 | offline | 76 | 21.032 | - |
3+
| resnet50 | offline | 76 | 21.023 | - |

open/MLCommons/measurements/gh_ubuntu-latest_x86-reference-cpu-tf_v2.20.0-default_config/resnet50/offline/README.md

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -16,7 +16,7 @@ pip install -U mlcflow
1616

1717
mlc rm cache -f
1818

19-
mlc pull repo mlcommons@mlperf-automations --checkout=591a5c664394d3553e039d5252d17163c0d7a0b1
19+
mlc pull repo mlcommons@mlperf-automations --checkout=ab6249733b0768eb8859778b7e1ac9f11b60a668
2020

2121

2222
```
@@ -40,4 +40,4 @@ Model Precision: fp32
4040
`acc`: `76.0`, Required accuracy for closed division `>= 75.6954`
4141

4242
### Performance Results
43-
`Samples per second`: `21.0316`
43+
`Samples per second`: `21.0227`
Lines changed: 9 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -1,12 +1,12 @@
1-
python3 python/main.py --profile resnet50-tf --model "/home/runner/MLC/repos/local/cache/download-file_ml-model-resnet_fcecf9c8/resnet50_v1.pb" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_077a6cd0 --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_a884e825/test_results/gh_ubuntu-latest x86-reference-cpu-tf-v2.20.0-default_config/resnet50/offline/accuracy" --scenario Offline --count 500 --threads 4 --user_conf /home/runner/MLC/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/f138a500d85042ac98a4f868bb2fc645.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_077a6cd0 --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_9798347b/val.txt
2-
INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_077a6cd0', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_9798347b/val.txt', data_format=None, profile='resnet50-tf', scenario='Offline', max_batchsize=32, model='/home/runner/MLC/repos/local/cache/download-file_ml-model-resnet_fcecf9c8/resnet50_v1.pb', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_a884e825/test_results/gh_ubuntu-latest x86-reference-cpu-tf-v2.20.0-default_config/resnet50/offline/accuracy', inputs=['input_tensor:0'], outputs=['ArgMax:0'], backend='tensorflow', device=None, model_name='resnet50', threads=4, qps=None, cache=0, cache_dir='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_077a6cd0', 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/f138a500d85042ac98a4f868bb2fc645.conf', audit_conf='audit.config', time=None, count=500, performance_sample_count=None, max_latency=None, samples_per_query=8)
3-
2025-09-21 08:05:51.594139: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.
4-
2025-09-21 08:05:51.639104: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
1+
python3 python/main.py --profile resnet50-tf --model "/home/runner/MLC/repos/local/cache/download-file_ml-model-resnet_00361dbf/resnet50_v1.pb" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_8a6540d1 --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_9064c4f5/test_results/gh_ubuntu-latest x86-reference-cpu-tf-v2.20.0-default_config/resnet50/offline/accuracy" --scenario Offline --count 500 --threads 4 --user_conf /home/runner/MLC/repos/mlcommons@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/36106956102e47c3ad44256cd7d66ba8.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_8a6540d1 --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_f9673c19/val.txt
2+
INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_8a6540d1', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_f9673c19/val.txt', data_format=None, profile='resnet50-tf', scenario='Offline', max_batchsize=32, model='/home/runner/MLC/repos/local/cache/download-file_ml-model-resnet_00361dbf/resnet50_v1.pb', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_9064c4f5/test_results/gh_ubuntu-latest x86-reference-cpu-tf-v2.20.0-default_config/resnet50/offline/accuracy', inputs=['input_tensor:0'], outputs=['ArgMax:0'], backend='tensorflow', device=None, model_name='resnet50', threads=4, qps=None, cache=0, cache_dir='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_8a6540d1', 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/36106956102e47c3ad44256cd7d66ba8.conf', audit_conf='audit.config', time=None, count=500, performance_sample_count=None, max_latency=None, samples_per_query=8)
3+
2025-09-25 17:39:46.296132: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.
4+
2025-09-25 17:39:46.343466: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
55
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
6-
2025-09-21 08:05:52.807021: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.
6+
2025-09-25 17:39:47.528262: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.
77
INFO:imagenet:Loading 500 preprocessed images using 4 threads
88
INFO:imagenet:loaded 500 images, cache=0, already_preprocessed=True, took=0.0sec
9-
WARNING:tensorflow:From /home/runner/MLC/repos/local/cache/get-git-repo_inference-src_c57762f4/inference/vision/classification_and_detection/python/backend_tf.py:55: FastGFile.__init__ (from tensorflow.python.platform.gfile) is deprecated and will be removed in a future version.
9+
WARNING:tensorflow:From /home/runner/MLC/repos/local/cache/get-git-repo_inference-src_b7ab4614/inference/vision/classification_and_detection/python/backend_tf.py:55: FastGFile.__init__ (from tensorflow.python.platform.gfile) is deprecated and will be removed in a future version.
1010
Instructions for updating:
1111
Use tf.gfile.GFile.
1212
WARNING:tensorflow:From /opt/hostedtoolcache/Python/3.12.11/x64/lib/python3.12/site-packages/tensorflow/python/tools/strip_unused_lib.py:84: extract_sub_graph (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
@@ -15,8 +15,8 @@ This API was designed for TensorFlow v1. See https://www.tensorflow.org/guide/mi
1515
WARNING:tensorflow:From /opt/hostedtoolcache/Python/3.12.11/x64/lib/python3.12/site-packages/tensorflow/python/tools/optimize_for_inference_lib.py:138: remove_training_nodes (from tensorflow.python.framework.graph_util_impl) is deprecated and will be removed in a future version.
1616
Instructions for updating:
1717
This API was designed for TensorFlow v1. See https://www.tensorflow.org/guide/migrate for instructions on how to migrate your code to TensorFlow v2.
18-
2025-09-21 08:06:52.086199: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)
18+
2025-09-25 17:40:43.913702: E external/local_xla/xla/stream_executor/cuda/cuda_platform.cc:51] failed call to cuInit: INTERNAL: CUDA error: Failed call to cuInit: UNKNOWN ERROR (303)
1919
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
20-
I0000 00:00:1758442012.171106 3984 mlir_graph_optimization_pass.cc:437] MLIR V1 optimization pass is not enabled
20+
I0000 00:00:1758822043.987835 4096 mlir_graph_optimization_pass.cc:437] MLIR V1 optimization pass is not enabled
2121
INFO:main:starting TestScenario.Offline
22-
TestScenario.Offline qps=0.67, mean=15.0514, time=23.858, acc=76.000%, queries=16, tiles=50.0:15.1868,80.0:22.7970,90.0:23.6159,95.0:23.7344,99.0:23.7624,99.9:23.7687
22+
TestScenario.Offline qps=0.67, mean=15.0328, time=23.833, acc=76.000%, queries=16, tiles=50.0:15.2725,80.0:22.8673,90.0:23.6521,95.0:23.6931,99.0:23.7329,99.9:23.7418

0 commit comments

Comments
 (0)