IMX93 NPU Dear NXP Community Experts/Engineers, Hello! Thank you for taking the time to review my question. I'm trying to use NPU to accelerate inference on the IMX9352 development board. -chip: imx9352 -yocto version: scarthgap 6.6.52 I read the document , followed the steps in Section 6.2.3, and the console output incorrect print information. commands: # cd /usr/bin/ethosu/examples # cp ../../tensorflow-lite-2.16.2/examples/labels.txt ./ # cp ../../tensorflow-lite-2.16.2/examples/grace_hopper.bmp ./ # vela ../../tensorflow-lite-2.16.2/examples/mobilenet_v1_1.0_224_quant.tflite # ./inference_runner -n ./output/mobilenet_v1_1.0_224_quant_vela.tflite -i grace_hopper.bmp -l labels.txt -o output.txt error message: root@imx93-11x11-lpddr4x-evk:/usr/bin/ethosu/examples# ./inference_runner -n ./output/mobilenet_v1_1.0_224_quant_vela.tflite -i grace_hopper.bmp -l labels.txt -o output.txt Send Ping Send version request Send capabilities request Capabilities: version_status:1 version:{ major=0, minor=0, patch=0 } product:{ major=6, minor=0, patch=0 } architecture:{ major=1, minor=0, patch=6 } driver:{ major=0, minor=16, patch=0 } macs_per_cc:8 cmd_stream_version:0 custom_dma:false Create network Error: IOCTL failed According to Section 8.1.2, the object detection case can run normally, but if the parameter "-d /usr/lib/libethosu_delegate.so" is added, it cannot run. here is the logs: root@imx93-11x11-lpddr4x-evk:/usr/bin/eiq-examples-git/object_detection# python3 main.py -i /dev/video1 -d /usr/lib/libethosu_delegate.so [ WARN:
[email protected]] global cap_gstreamer.cpp:2839 handleMessage OpenCV | GStreamer warning: Embedded video playback halted; module source reported: Could not read from resource. [ WARN:
[email protected]] global cap_gstreamer.cpp:1698 open OpenCV | GStreamer warning: unable to start pipeline [ WARN:
[email protected]] global cap_gstreamer.cpp:1173 isPipelinePlaying OpenCV | GStreamer warning: GStreamer: pipeline have not been created INFO: Ethosu delegate: device_name set to /dev/ethosu0. INFO: Ethosu delegate: cache_file_path set to . INFO: Ethosu delegate: timeout set to 60000000000. INFO: Ethosu delegate: enable_cycle_counter set to 0. INFO: Ethosu delegate: enable_profiling set to 0. INFO: Ethosu delegate: profiling_buffer_size set to 2048. INFO: Ethosu delegate: pmu_event0 set to 0. INFO: Ethosu delegate: pmu_event1 set to 0. INFO: Ethosu delegate: pmu_event2 set to 0. INFO: Ethosu delegate: pmu_event3 set to 0. INFO: EthosuDelegate: 108 nodes delegated out of 111 nodes with 1 partitions. INFO: Created TensorFlow Lite XNNPACK delegate for CPU. Traceback (most recent call last): File "/usr/bin/eiq-examples-git/object_detection/main.py", line 68, in interpreter.invoke() File "/usr/lib/python3.12/site-packages/tflite_runtime/interpreter.py", line 941, in invoke self._interpreter.Invoke() RuntimeError: Ethos_u inference failed Node number 111 (EthosuDelegate) failed to invoke. I want to know how to test whether my NPU can work properly and how to use it correctly for accelerated inference. I have an object detection model, detect.tflite(SSD_V2), and I hope to use the NPU on IMX93 to accelerate the inference function of this model. The complete print information can be found in the attachment "logs.txt". Thank you again for your assistance! Please let me know if you need any additional information.I will provide it promptly. Best regards, James Linux
