Nano_machine_learning_test_result
Processor: ARMv8 Cortex-A78E @ 1.51GHz (6 Cores), Motherboard: EDK II 3.1-32827747, Memory: 8GB, Disk: 256GB TEAM Ind N745-M80W, Graphics: NVIDIA Tegra Orin, Monitor: BenQ GW2381, Network: Realtek RTL8111/8168/8411 + Realtek RTL8822CE 802.11ac PCIe
OS: Ubuntu 20.04, Kernel: 5.10.104-tegra (aarch64), Desktop: GNOME Shell 3.36.9, Display Server: X Server 1.20.13, Display Driver: NVIDIA 35.3.1, OpenGL: 4.6.0, Vulkan: 1.3.212, Compiler: GCC 9.4.0 + CUDA 11.4, File-System: ext4, Screen Resolution: 1920x1200
Kernel Notes: Transparent Huge Pages: always
Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-target-system-zlib=auto -v
Processor Notes: Scaling Governor: tegra194 schedutil
Python Notes: Python 2.7.18 + Python 3.8.10
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of __user pointer sanitization + spectre_v2: Not affected + srbds: Not affected + tsx_async_abort: Not affected
AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.
machine_learning_test_result: The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
This is a benchmark of the Caffe deep learning framework and currently supports the AlexNet and Googlenet model and execution on both CPUs and NVIDIA GPUs. Learn more via the OpenBenchmarking.org test page.
Model: AlexNet - Acceleration: CPU - Iterations: 100
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./caffe: 3: ./tools/caffe: not found
Model: AlexNet - Acceleration: CPU - Iterations: 200
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./caffe: 3: ./tools/caffe: not found
Model: AlexNet - Acceleration: CPU - Iterations: 1000
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./caffe: 3: ./tools/caffe: not found
Model: GoogleNet - Acceleration: CPU - Iterations: 100
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./caffe: 3: ./tools/caffe: not found
Model: GoogleNet - Acceleration: CPU - Iterations: 200
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./caffe: 3: ./tools/caffe: not found
Model: GoogleNet - Acceleration: CPU - Iterations: 1000
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./caffe: 3: ./tools/caffe: not found
The CANDLE benchmark codes implement deep learning architectures relevant to problems in cancer. These architectures address problems at different biological scales, specifically problems at the molecular, cellular and population scales. Learn more via the OpenBenchmarking.org test page.
Benchmark: P1B2
machine_learning_test_result: The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Benchmark: P3B1
machine_learning_test_result: The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Benchmark: P3B2
machine_learning_test_result: The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.
Mlpack benchmark scripts for machine learning libraries Learn more via the OpenBenchmarking.org test page.
Benchmark: scikit_ica
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'float'.
Benchmark: scikit_qda
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'float'.
Benchmark: scikit_svm
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'float'.
Benchmark: scikit_linearridgeregression
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'float'.
MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.
NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.
This is a benchmark of Neural Magic's DeepSparse using its built-in deepsparse.benchmark utility and various models from their SparseZoo (https://sparsezoo.neuralmagic.com/). Learn more via the OpenBenchmarking.org test page.
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: cannot import name 'TypeAliasType' from 'typing_extensions' (/usr/local/lib/python3.8/dist-packages/typing_extensions.py)
Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial time-series data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.
This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.
This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
machine_learning_test_result: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
machine_learning_test_result: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
machine_learning_test_result: The test run did not produce a result. The test run did not produce a result. The test run did not produce a result.
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
ONNX Runtime is developed by Microsoft and partners as a open-source, cross-platform, high performance machine learning inferencing and training accelerator. This test profile runs the ONNX Runtime with various models available from the ONNX Model Zoo. Learn more via the OpenBenchmarking.org test page.
Model: GPT-2 - Device: CPU - Executor: Parallel
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: GPT-2 - Device: CPU - Executor: Standard
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: yolov4 - Device: CPU - Executor: Parallel
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: yolov4 - Device: CPU - Executor: Standard
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: bertsquad-12 - Device: CPU - Executor: Parallel
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: bertsquad-12 - Device: CPU - Executor: Standard
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: CaffeNet 12-int8 - Device: CPU - Executor: Parallel
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: CaffeNet 12-int8 - Device: CPU - Executor: Standard
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: fcn-resnet101-11 - Device: CPU - Executor: Standard
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Parallel
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: ResNet50 v1-12-int8 - Device: CPU - Executor: Standard
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: super-resolution-10 - Device: CPU - Executor: Parallel
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: super-resolution-10 - Device: CPU - Executor: Standard
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Parallel
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Standard
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./onnx: line 2: ./onnxruntime/build/Linux/Release/onnxruntime_perf_test: No such file or directory
This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests. Learn more via the OpenBenchmarking.org test page.
This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.
FP16: No - Mode: Inference - Network: VGG16 - Device: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./plaidml: line 24: /.local/bin/plaidbench: No such file or directory
FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ./plaidml: line 24: /.local/bin/plaidbench: No such file or directory
This test is a quick-running survey of general R performance Learn more via the OpenBenchmarking.org test page.
RNNoise is a recurrent neural network for audio noise reduction developed by Mozilla and Xiph.Org. This test profile is a single-threaded test measuring the time to denoise a sample 26 minute long 16-bit RAW audio file using this recurrent neural network noise suppression library. Learn more via the OpenBenchmarking.org test page.
Scikit-learn is a Python module for machine learning built on NumPy, SciPy, and is BSD-licensed. Learn more via the OpenBenchmarking.org test page.
Benchmark: Glmnet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'glmnet'
Benchmark: SGDOneClassSVM
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Benchmark: Isolation Forest
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Benchmark: Plot Fast KMeans
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status.
Benchmark: Isotonic / Logistic
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
Benchmark: Plot Incremental PCA
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: Matplotlib requires numpy>=1.20; you have 1.17.4
Benchmark: Hist Gradient Boosting
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: Matplotlib requires numpy>=1.20; you have 1.17.4
Benchmark: Plot Parallel Pairwise
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: Matplotlib requires numpy>=1.20; you have 1.17.4
Benchmark: Isotonic / Pathological
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
Benchmark: RCV1 Logreg Convergencet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: Matplotlib requires numpy>=1.20; you have 1.17.4
Benchmark: Sample Without Replacement
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: Matplotlib requires numpy>=1.20; you have 1.17.4
Benchmark: Covertype Dataset Benchmark
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
Benchmark: Hist Gradient Boosting Adult
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy.random' has no attribute 'BitGenerator'
Benchmark: Isotonic / Perturbed Logarithm
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
Benchmark: Hist Gradient Boosting Threading
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
Benchmark: Plot Singular Value Decomposition
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
Benchmark: Hist Gradient Boosting Higgs Boson
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy.random' has no attribute 'BitGenerator'
Benchmark: 20 Newsgroups / Logistic Regression
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
Benchmark: Plot Polynomial Kernel Approximation
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
Benchmark: Plot Non-Negative Matrix Factorization
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: Matplotlib requires numpy>=1.20; you have 1.17.4
Benchmark: Hist Gradient Boosting Categorical Only
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
Benchmark: Kernel PCA Solvers / Time vs. N Samples
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: Matplotlib requires numpy>=1.20; you have 1.17.4
Benchmark: Kernel PCA Solvers / Time vs. N Components
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ImportError: Matplotlib requires numpy>=1.20; you have 1.17.4
Benchmark: Sparse Random Projections / 100 Iterations
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 232 from C header, got 216 from PyObject
The spaCy library is an open-source solution for advanced neural language processing (NLP). The spaCy library leverages Python and is a leading neural language processing solution. This test profile times the spaCy CPU performance with various models. Learn more via the OpenBenchmarking.org test page.
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.
Device: CPU - Batch Size: 16 - Model: VGG-16
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 32 - Model: VGG-16
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 64 - Model: VGG-16
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 16 - Model: AlexNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 256 - Model: VGG-16
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 32 - Model: AlexNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 512 - Model: VGG-16
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 64 - Model: AlexNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 256 - Model: AlexNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 512 - Model: AlexNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 16 - Model: GoogLeNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 16 - Model: ResNet-50
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 32 - Model: GoogLeNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 32 - Model: ResNet-50
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 64 - Model: GoogLeNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 64 - Model: ResNet-50
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 256 - Model: GoogLeNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 256 - Model: ResNet-50
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 512 - Model: GoogLeNet
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
Device: CPU - Batch Size: 512 - Model: ResNet-50
machine_learning_test_result: The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'bool'.
This is a benchmark of the TensorFlow Lite implementation focused on TensorFlow machine learning for mobile, IoT, edge, and other cases. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.
TNN is an open-source deep learning reasoning framework developed by Tencent. Learn more via the OpenBenchmarking.org test page.
Processor: ARMv8 Cortex-A78E @ 1.51GHz (6 Cores), Motherboard: EDK II 3.1-32827747, Memory: 8GB, Disk: 256GB TEAM Ind N745-M80W, Graphics: NVIDIA Tegra Orin, Monitor: BenQ GW2381, Network: Realtek RTL8111/8168/8411 + Realtek RTL8822CE 802.11ac PCIe
OS: Ubuntu 20.04, Kernel: 5.10.104-tegra (aarch64), Desktop: GNOME Shell 3.36.9, Display Server: X Server 1.20.13, Display Driver: NVIDIA 35.3.1, OpenGL: 4.6.0, Vulkan: 1.3.212, Compiler: GCC 9.4.0 + CUDA 11.4, File-System: ext4, Screen Resolution: 1920x1200
Kernel Notes: Transparent Huge Pages: always
Compiler Notes: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-target-system-zlib=auto -v
Processor Notes: Scaling Governor: tegra194 schedutil
Python Notes: Python 2.7.18 + Python 3.8.10
Security Notes: itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of __user pointer sanitization + spectre_v2: Not affected + srbds: Not affected + tsx_async_abort: Not affected
Testing initiated at 24 July 2023 03:56 by user root.