(pid: 205534) error_file: <N/A> traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html --- Root Cause (first observed failure): [0]: time : 2024-02-22_14:35:53 host : dl-231116164921eba-pod-jupyter-b8f66cdd9-knmld rank : 0 (local_rank: 0...
Your current environment Environment in the container: INFO 04-29 06:34:01 [init.py:239] Automatically detected platform cuda. Collecting environment information... PyTorch version: 2.6.0+cu124 Is debug build: False CUDA used to build Py...
"input_ids=tokenizer.encode(prompt,return_tensors="pt")model.eval()traced_model=torch.fx.symbolic_trace(model)m=fx.export_and_import(traced_model, (input_ids,),enable_ir_printing=True,enable_graph_printing=True)withopen("qwen1.5b_s.mlir","w")asf:f.write(str(m)) Traceback (most recen...
Other info[0]:time=2023-09-28-02:17:58.010.670, function=send_timeout_cq_msg_with_result, line=1383, error code=0x25Traceback (most recent call last): File "train_npu.py", line 38, in train() File "/media/sda/shengteng_test/ModelZoo-PyTorch/PyTorch/built-in/foundation/Baichuan2/...
PyTorch Forums – 6 May 18 Cuda Error : RuntimeError: CUDNN_STATUS_EXECUTION_FAILED I am trying to run a simple RNN model with LSTM unit but I am getting cuda error (same code is working fine with CPU) Rnn model is like below class BiRNN(nn.Module): ...
failed to execute graph. model_id = 3[FUNC:HandleResult][FILE:hybrid_model_async_executor.cc][LINE:217] [[{{node GeOp9_0}}]] During handling of the above exception, another exception occurred: Traceback (most recent call last):
Error traceback这是pytorch转tensorRT模型的日志 This is the log of pytorch to tensorRT model 2022-07-21 09:57:35,423 - mmdeploy - INFO - 当前任务ID:bcccd9e0-41a1-408d-9dfa-f4e634e9608c Registry:{'input_size': (640, 640), 'random_size_range': (15, 25), 'random_size_interval'...
Exact steps/commands to run your repro Full traceback of errors encountered NVES Hi, Request you to share the ONNX model and the script if not shared already so that we can assist you better. Alongside you can try few things: docs.nvidia.com ...
time benchmark model execution time Flags from tools/caffe.cpp: -gpu (Optional; run in GPU mode on given device IDs separated by ','.Use '-gpu all' to run on all available GPUs. The effective training batch size is multiplied by the number of devices.) type: string default: "" -ite...
将pytorch模型.pth导出为onnx格式时报错,源代码如下: 错误信息如下 Traceback (most recent call last): File "111.py", line 17, in <module> torch.onnx.export(model,dummy_input,"yolov3.onnx",input_names=['images'],output_names=['outTensors'],export_params=True,training=False) ...