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| Model | Scenario | Accuracy | Throughput | Latency (in ms) |
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|----------|------------|------------|--------------|-------------------|
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| resnet50 | offline | 76 | 21.137 | - |
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| resnet50 | offline | 76 | 21.055 | - |

open/MLCommons/measurements/gh_ubuntu-latest_x86-reference-cpu-tf_v2.19.0-default_config/resnet50/offline/README.md

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mlc rm cache -f
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mlc pull repo mlcommons@mlperf-automations --checkout=8fb919a86d629e93ad125991bda291016e7fbe5e
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mlc pull repo anandhu-eng@mlperf-automations --checkout=cdff188b845b59537104c7f2faa6aba3dffca200
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```
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*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf,
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you should simply reload mlcommons@mlperf-automations without checkout and clean MLC cache as follows:*
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you should simply reload anandhu-eng@mlperf-automations without checkout and clean MLC cache as follows:*
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```bash
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mlc rm repo mlcommons@mlperf-automations
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mlc pull repo mlcommons@mlperf-automations
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mlc rm repo anandhu-eng@mlperf-automations
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mlc pull repo anandhu-eng@mlperf-automations
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mlc rm cache -f
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```
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`acc`: `76.0`, Required accuracy for closed division `>= 75.6954`
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### Performance Results
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`Samples per second`: `21.1373`
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`Samples per second`: `21.055`
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python3 python/main.py --profile resnet50-tf --model "/home/runner/MLC/repos/local/cache/download-file_ml-model-resnet_ac2119b4/resnet50_v1.pb" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_00c832e4 --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_27651a56/test_results/gh_ubuntu-latest x86-reference-cpu-tf-v2.19.0-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/15140984966247728fa3c53eb01b22e5.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_00c832e4 --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_503f09f9/val.txt
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INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_00c832e4', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_503f09f9/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_ac2119b4/resnet50_v1.pb', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_27651a56/test_results/gh_ubuntu-latest x86-reference-cpu-tf-v2.19.0-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_00c832e4', 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/15140984966247728fa3c53eb01b22e5.conf', audit_conf='audit.config', time=None, count=500, performance_sample_count=None, max_latency=None, samples_per_query=8)
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2025-07-13 15:03:23.248716: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.
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2025-07-13 15:03:23.251882: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.
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2025-07-13 15:03:23.260377: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
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python3 python/main.py --profile resnet50-tf --model "/home/runner/MLC/repos/local/cache/download-file_ml-model-resnet_16d8430d/resnet50_v1.pb" --dataset-path /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_befc90f1 --output "/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_b79713bc/test_results/gh_ubuntu-latest x86-reference-cpu-tf-v2.19.0-default_config/resnet50/offline/accuracy" --scenario Offline --count 500 --threads 4 --user_conf /home/runner/MLC/repos/anandhu-eng@mlperf-automations/script/generate-mlperf-inference-user-conf/tmp/46945951a16140bfbfbeb869ca84bd59.conf --accuracy --use_preprocessed_dataset --cache_dir /home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_befc90f1 --dataset-list /home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_14d806cc/val.txt
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INFO:main:Namespace(dataset='imagenet', dataset_path='/home/runner/MLC/repos/local/cache/get-preprocessed-dataset-imagenet_befc90f1', dataset_list='/home/runner/MLC/repos/local/cache/extract-file_imagenet-aux-da_14d806cc/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_16d8430d/resnet50_v1.pb', output='/home/runner/MLC/repos/local/cache/get-mlperf-inference-results-dir_b79713bc/test_results/gh_ubuntu-latest x86-reference-cpu-tf-v2.19.0-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_befc90f1', 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/46945951a16140bfbfbeb869ca84bd59.conf', audit_conf='audit.config', time=None, count=500, performance_sample_count=None, max_latency=None, samples_per_query=8)
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2025-07-15 07:23:58.285457: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.
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2025-07-15 07:23:58.288702: I external/local_xla/xla/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.
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2025-07-15 07:23:58.297494: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
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WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
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E0000 00:00:1752419003.274546 7925 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
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E0000 00:00:1752419003.278851 7925 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
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W0000 00:00:1752419003.290298 7925 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
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W0000 00:00:1752419003.290315 7925 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
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W0000 00:00:1752419003.290317 7925 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
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W0000 00:00:1752419003.290319 7925 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
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2025-07-13 15:03:23.293941: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
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E0000 00:00:1752564238.311664 7916 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
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E0000 00:00:1752564238.316286 7916 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
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W0000 00:00:1752564238.328052 7916 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
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W0000 00:00:1752564238.328069 7916 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
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W0000 00:00:1752564238.328073 7916 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
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W0000 00:00:1752564238.328075 7916 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.
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2025-07-15 07:23:58.331870: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
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To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
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INFO:imagenet:Loading 500 preprocessed images using 4 threads
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INFO:imagenet:loaded 500 images, cache=0, already_preprocessed=True, took=0.0sec
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WARNING:tensorflow:From /home/runner/MLC/repos/local/cache/get-git-repo_inference-src_caeb4811/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.
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WARNING:tensorflow:From /home/runner/MLC/repos/local/cache/get-git-repo_inference-src_b600f3c5/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.
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Instructions for updating:
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Use tf.gfile.GFile.
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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.
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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.
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Instructions for updating:
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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.
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2025-07-13 15:04:20.301841: 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)
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2025-07-15 07:24:56.009944: 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)
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WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
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I0000 00:00:1752419060.342732 7925 mlir_graph_optimization_pass.cc:425] MLIR V1 optimization pass is not enabled
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I0000 00:00:1752564296.076553 7916 mlir_graph_optimization_pass.cc:425] MLIR V1 optimization pass is not enabled
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INFO:main:starting TestScenario.Offline
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TestScenario.Offline qps=0.68, mean=14.9325, time=23.676, acc=76.000%, queries=16, tiles=50.0:15.1540,80.0:22.9020,90.0:23.4747,95.0:23.5293,99.0:23.5711,99.9:23.5805
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TestScenario.Offline qps=0.67, mean=14.9598, time=23.738, acc=76.000%, queries=16, tiles=50.0:14.9405,80.0:22.7372,90.0:23.5127,95.0:23.6059,99.0:23.6364,99.9:23.6433

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