OSError: (External) CUDA error(3), initialization error. [Hint: 'cudaErrorInitializationError'. The API call failed because the CUDA driver and runtime could not be initialized. ] (at /paddle/paddle/fluid/platform/gpu_info.cc:355) [pid: 508038|app: 0|req: 2/2] 124.160.31.180 () {48...
$(error “CUDA_VER is not set”) endif APP:= deepstream-testsr-app TARGET_DEVICE = $(shell gcc -dumpmachine | cut -f1 -d -) NVDS_VERSION:=6.0 LIB_INSTALL_DIR?=/opt/nvidia/deepstream/deepstream-$(NVDS_VERSION)/lib/ APP_INSTALL_DIR?=/opt/nvidia/deepstream/deepstream-$(NVDS_VERSION)...
As you can see here, running time forTensorrtExecutionProvideris more thanCUDAExecutionProviderandCPUExecutionProvidermodes. Also output of TensorrtExecutionProvider and CUDAExecutionProvider are equal, while should not be
另外,官方编译的版本中,缺少 jni 库 onnxruntime4j_jni.dll,无法直接被 java API 调用。如果使用未联合编译的 jni 库,会报这样一条异常: ai.onnxruntime.OrtException: Error code - ORT_INVALID_ARGUMENT - message: This binary was not compiled with OpenVINO support. 官方jar包解压缩后 EP 官方手册 ...
TRT Warning: Could not find TensorRT WARNING: All log messages beforeabsl::InitializeLog() is called are written to STDERR I0000 00:00:1728650506.662098 1240 cuda_executor.cc:1001] could not open file toreadNUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node Your kernel may have been ...
If you left things at the default settings then it should be named <application name>.exe.embed.manifest and it should be in the same directory as the object files. This is a signature Any samples given are not meant to have error checking or show best practices. They are meant to j...
rw -v ~/docker/isaac-sim/config:/root/.nvidia-omniverse/config:rw -v ~/docker/isaac-sim/data:/root/.local/share/ov/data:rw -v ~/docker/isaac-sim/documents:/root/Documents:rw nvcr.io/nvidia/isaac-sim:2022.1.0 docker: Error response from daemon: could not s...
Steps to reproduce: Run a Docker container using ollama/ollama:rocm on a machine with a single MI300X Inside the container, run ollama run llama3.1:70B Actual behaviour: rocBLAS error: Could not initialize Tensile host: No devices found ...
CUDA Version: 11.2 (Driver Version) / 10.2 (Runtime Version) CUDNN Version: cudnn-10.2 Operating System + Version: Windows 10 Pro Python Version (if applicable): 3.7.11 TensorFlow Version (if applicable): 1.15.0 Output Log: This is the Output error list...
However, the terminal is still very slow at this step. Applied providers: ['CUDAExecutionProvider', 'CPUExecutionProvider'], with options: {'CUDAExecutionProvider': {'cudnn_conv_algo_search': 'EXHAUSTIVE', 'device_id': '0', 'has_user_compute_stream': '0', 'cudnn_conv1d_pad_to_nc1...