dnn Suite
1.0.0
System
Test suite extracted from dnn.
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_1d --cfg=bf16bf16bf16 --engine=cpu
Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-2.7.0
--ip --batch=inputs/ip/shapes_3d --cfg=bf16bf16bf16 --engine=cpu
Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-2.7.0
--conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
pts/y-cruncher-1.2.0
1b
Pi Digits To Calculate: 1B
pts/onednn-2.7.0
--conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--conv --batch=inputs/conv/shapes_auto --cfg=bf16bf16bf16 --engine=cpu
Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_1d --cfg=bf16bf16bf16 --engine=cpu
Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-2.7.0
--deconv --batch=inputs/deconv/shapes_3d --cfg=bf16bf16bf16 --engine=cpu
Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-2.7.0
--rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
pts/onednn-2.7.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
pts/onednn-2.7.0
--matmul --batch=inputs/matmul/shapes_transformer --cfg=bf16bf16bf16 --engine=cpu
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU
pts/aom-av1-3.5.0
--cpu-used=0 --limit=20 Bosphorus_3840x2160.y4m
Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=4 Bosphorus_3840x2160.y4m
Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=6 --rt Bosphorus_3840x2160.y4m
Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=6 Bosphorus_3840x2160.y4m
Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=8 --rt Bosphorus_3840x2160.y4m
Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=9 --rt Bosphorus_3840x2160.y4m
Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=10 --rt Bosphorus_3840x2160.y4m
Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K
pts/aom-av1-3.5.0
--cpu-used=0 --limit=20 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m
Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p
pts/aom-av1-3.5.0
--cpu-used=4 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m
Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p
pts/aom-av1-3.5.0
--cpu-used=6 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m
Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p
pts/aom-av1-3.5.0
--cpu-used=6 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m
Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p
pts/aom-av1-3.5.0
--cpu-used=8 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m
Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p
pts/aom-av1-3.5.0
--cpu-used=9 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m
Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p
pts/aom-av1-3.5.0
--cpu-used=10 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m
Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p